<figure><img src="image_44.png" /><figcaption>Fig. 40 LP-MIME transceiver block diagram</figcaption></figure>

surfaces can be several tens of volts (Holmberg 2020; Bochet et al. 2023; Holmberg et al. 2024). Probe electronics must cope with those potential differences. That is achieved by using floating power supply techniques for the first stages of both E-field and LP electronics.

The probe potential in E-field mode is anchored tightly to the local plasma potential (reference potential in the plasma) and do not depend on the plasma parameters. To achieve this, a constant bias current is injected into the plasma, moving the probe quiescent point as close as possible to the plasma potential. In Density mode, the probe bias voltage is set to a preferable quiescent point on the local Langmuir curve.

A sweep of current in E-field mode or voltage in Density mode is used to obtain correct quiescent point settings for all probes. Traditional Langmuir sweeps are used to obtain local plasma parameters.

MIME is an active multi-pole instrument, which measures plasma impedance (Z). The experiment is composed of different transmission and reception electrodes, a sine wave generator, and a receiver.

The measurement principle is based on Ohm's law $Z=V/I$ applied to the system formed by the electrodes and the surrounding plasma. By applying a sinusoidal signal at a given frequency on one or two transmission electrodes, an AC current (I) is forced inside the plasma. The sine wave generator transmits a signal of constant amplitude over several periods. After plasma stabilization, MIME measures the potential difference (V) between two reception electrodes to get access to the mutual impedance (Z) at the transmitted frequency, as illustrated on Fig. 42. The transmitted signal and reception signal are internally synchronized inside the FPGA of the receiver, which gives us the knowledge of the phase of the mutual impedance, a piece of important information to derive the plasma parameters. When MIME
<figure><img src="image_45.png" /><figcaption>**Fig. 41** LP-MIME digital block diagram</figcaption></figure>

<figure><img src="image_46.png" /><figcaption>**Fig. 42** MIME measurement principle</figcaption></figure>

uses two transmission electrodes, the same signal, but in phase opposition, is sent to both transmitters.

By sweeping the transmitted frequency over a frequency interval containing the plasma resonances, MIME constructs a frequency impedance spectrum whose features reflect the plasma characteristics. After post-processing of the raw data by the DPU, the impedance spectra are sent to the ground where they can be analyzed to derive the properties of the
<figure><img src="image_47.png" /><figcaption>Fig. 43 MIME transmitter drivers</figcaption></figure>

thermal component of the plasma such as electron density and, in certain conditions, electron temperature.

For low and medium frequency measurement (3 kHz up to 1.5 MHz), MIME uses the four Langmuir probes as transmitting/receiving electrodes together with the LP-MIME receiver to generate the transmission signal and perform the potential differential measurements.

Internally to the LP-MIME board, the transmission signal is generated and sent to the MIME transceiver. The MIME transceiver is a part of the LP-MIME receiver. The purpose of this sub-system is to filter the high frequency, amplify (4 gains) the signal, create the 180° phase shift for the second transmission signals (if used) and route the signals to one or two corresponding transmission Langmuir probes (see Fig. 43).

As shown in Fig. 44, for low and medium frequency measurement, there are two ways to carry out measurements by using the LP-MIME receiver. In case (A), the transmission signal is sent to one pair of Langmuir probes (red) and received by the other pair of Langmuir probes (green). In case (B), the transmission signal is sent to only one Langmuir probe (red) and received by one or two pairs formed by the other Langmuir probes (green).

The bandwidth can be extended to higher frequencies (from 80 kHz to 3 MHz) by using the RWI receiver and RWI antennas as follows. The RWI receiver generates the transmission signal which is routed to LP-MIME board to MIME transceiver to send the signal to the Langmuir probes (transmission sensors), while the measurement is performed on RWI antennas (reception sensors).

As shown in Fig. 45, there are two ways to perform high frequency measurements using the LP-MIME receiver as transmitter and RWI receiver. In case (C), the transmission signal from RWI receiver is sent to one pair of Langmuir probes (red) and received by one, two or three RWI antennas (green). In case (D), the transmission signal is sent to only one Langmuir probe (red) and received by one, two or three RWI dipolar antennas (green).

To ensure optimal modularity and enable MIME to easily adapt to the various scientific objectives of RPWI, it is possible to select any probes in transmission and reception. This results in a total of 96 possible antenna configurations (LP + RWI). In regular MIME operations, only a few configurations are expected to be used for science purposes.

Finally, although the Langmuir probes and the RWI antennas are the primary sensors used by MIME, any magnetic or electric field sensor can be employed. Therefore, the reception signal can be sampled by the LP, LF, and HF receivers and used for internal RPWI calibration purposes.
<figure><img src="image_48.png" /><figcaption>**Fig. 44** MIME transmission/reception modes in low and medium frequency mode: (A) transmission (red) on one pair of Langmuir probes, reception (green) on one pair of Langmuir probes. (B) transmission (red) on one Langmuir probe, reception (green) on one or two pairs of Langmuir probes</figcaption></figure>

### 4.2.6 LF Receiver

The LF receiver subsystem implements multidimensional onboard analysis of signals generated by the SCM and LP-PWI sensors at frequencies below 20 kHz (Fig. 46). The purpose of the LF receiver is to digitize and pre-process these signals for obtaining information on power, polarization, and propagation properties of fluctuating electromagnetic field and plasma parameters in the Jovian magnetosphere, in vicinity of Jovian icy moons and, especially, in the magnetosphere of Ganymede. The LF receiver performs computationally intense first stage onboard processing in an FPGA, while the more sophisticated second stage processing is implemented by a dedicated part of the RPWI flight software executing on the DPU. This two-stage processing yields a compressed data flow, effectively using the scarce telemetry resources.

The on-board analysis of low-frequency signals by the LF receiver is based on three magnetic field input signals from SCM, and on signals from the four Langmuir probes routed to LF from the LP-PWI subunit (density mode and electric field more signals are routed independently). Before digitization, all the signals are low pass filtered by identical 4th order analogue anti-aliasing filters with a cut-off at approximately 50 kHz. Furthermore, the LP-PWI signals are high-pass filtered with a cut-off of about 50 Hz to remove low frequency signal variations.

Digitization of the signals is performed by eight 14-bit analogue-to-digital converters (ADC). While the three SCM inputs are directly allocated to specific ADCs, the LP inputs
<figure><img src="image_49.png" /><figcaption>**Fig. 45** MIME transmission modes in high-frequency mode: (C) transmission (red) on one pair of Langmuir probes and reception (green) on RWI antennas, (D) transmission (red) on one Langmuir probe and reception (green) on RWI antennas</figcaption></figure>

(E-field and Density) are routed through a bank of analogue multiplexers and differential amplifiers allowing a variety of input signals to be sampled by the remaining 5 ADCs. The LF can thus sample combinations of E or D signals, an analogue sum of several probe potentials or differential E-field signals (differential voltages between pairs of LP probes).

All signals are oversampled at a base frequency of 781,250 Hz and further decimated and filtered in the FPGA to gain a better dynamic range. For D/E/B signals, a combination of cascaded integrator–comb (CIC) and FIR filters with a combined factor of 16 or 32 is used to obtain the final digital signal at 48,828 or 24,414 samples per second. The LF receiver allows to capture a snapshot of this waveform (up to 262,144 samples per channel) and store it in an internal memory to be later transmitted to the RPWI DPU. This same time series is then used to calculate averaged Fourier spectral matrices composed of auto-spectra and cross spectra of the 8 components. This calculation is done in the FPGA using a 2048 point fixed precision FFT, followed by cross-spectra calculation and averaging both in time and in frequency into a set of predefined frequency bands configurable by a telecommand. The LF FPGA also implements further decimation of the signals by another combination of CIC and FIR filters to obtain a continuous low frequency waveform sampled at 762.9 samples per second.

The second-stage data processing layer implemented in the application software of the RPWI DPU further treats the intermediate data products from the LF board to produce
<figure><img src="image_50.png" /><figcaption>Fig. 46 LF receiver block diagram</figcaption></figure>

the final science telemetry in an efficient format. See Sect. 5.6 for a description of the LF software.

### 4.2.7 HF Receiver

The HF receiver covers the highest frequency end of the RPWI, which implements analysis of the three-dimensional electric field vector in the 0.08–45 MHz range. The received signals are generated by the three orthogonal electric dipole antennas (RWI, see Sects. 4.2.12 and 4.2.13). As shown in the block diagram in Fig. 47, the HF receiver consists of two parts, HF-Analogue and HF-Digital.

HF-Analogue implements the analogue signal chain with low-path filter (8th order Butterworth, 45-MHz cut-off). After that the signal is amplified with +9 dB, which enables to see the RWI preamp noise floor with a few dB margin.

HF-Digital is a direct sampling, software defined radio (SDR), which implements the analogue to digital conversion, down mixing, and decimation filtering. First, the analogue signal chain gets digitized by 14-bit ADCs running at 90 Msps. Digitalized data stream gets multiplied with the two numeric local oscillator (NCO) signals, Cosine and Sine, to bring the centre frequency of interest to baseband (0 Hz). The signal is now complex valued and contains both positive and negative frequencies. The real (I) and imaginary (Q) parts of the signals are thereafter processed through CIC decimation, and later, FIR filters, where the final output sample rate can be adjusted stepwise from 298 ksps down to 18.6 ksps. The sample rate (and output bandwidth) is reduced by a factor of two in each step and the dynamic range is increased to 100 dB or better. The 20-bit signed *I* & *Q* output data is buffered and sent as packets over the serial link to the DPU board.

The problem of this HFR design is the high-power consumption associated with high sampling rate. If we try to operate continuous sampling, the peak power becomes ~7 W, which impacts the operating temperature of the HF FPGA and ADCs. In most of the observations, the sampling is as sparse as possible (once per 10 – several 10 seconds) and the 90-MHz clock and ADC are stopped between this term. In this ‘standby-mode’, HFR only
<figure><img src="image_51.png" /><figcaption>Fig. 47 HF receiver block diagram</figcaption></figure>

consumes ~0.5 W so that the semi-continuous long-term monitoring can be operated. With this operation, we will operate the HFR with the averaged power of ~0.7 W in the normal magnetosphere monitoring, <1 W for the passive radar observations of icy moon crusts, and a few W for the radio occultation of icy moon ionospheres.

The HF system (JENRAGE) also contains the HF software (HF-DPU) installed into the DPU for further processing of the down-converted *I* and *Q* signals. Since raw telemetry from HFR is huge, further telemetry processing by the DPU-HF software is critical for a compressed data flow. See Sect. 5.8 for a description of the HF software.

As shown in Fig. 47, the HFR provides the driving power, the internal heater-power, and the calibration signals to the RWI preamp (see Sect. 4.2.13). The HFR also provides the route and control of the deployment power and the survival heater power to the RWI antennas (28 V).

MIME HF measurement from 80 kHz up to 3 MHz (as described Sect. 4.2.7) make use of the Langmuir probes to transmit a signal and reception with the RWI antennas. To synchronize the MIME HF measurements, the HF receiver sends its mixer frequency (MIME Tx) to the MIME subsystem, which is located on the LP-PWI transceiver board.

### 4.2.8 LP-PWI Booms & Probes

LP-PWI consists of four identical deployable booms located individually on various sides of the JUICE S/C. Each consists of two composite CFRP limbs connected with hinges and has ultra-light mass of 1.2 kg (Ossowski et al. 2021). Due to the low mass budget, the booms are actuated by the drive springs without a damper, and therefore they utilize their elasticity to compensate for the residual end deployment shock energy. They deploy and position each of four Langmuir Probes three meters from the spacecraft at a 135-degree angle from the initial position.
<figure><img src="image_52.png" /><figcaption>**Fig. 48.** (Top) LP-PWI Boom subassemblies in a deployment phase. (Bottom) One of the as-built flight models in the stowed configuration</figcaption></figure>

The LP-PWI unit consists of four major subassemblies: Base (which consists of two Hold Down Release Mechanisms – HDRMs), Link 1, Link 2, and the sensor – the Langmuir Probe Assembly. There are connections between these subassemblies: the Base Hinge, which connects Base and Link 1, and the Central Hinge, which connects Link 1 and Link 2. The configuration of subassemblies is shown in Fig. 48. In the stowed configuration, shown at the bottom of the Figure, the links are held by HDRMs utilizing Vectran string and thermal knife technology. Once released on the orbit, the CFRP links start to deploy in a proper sequence (first central hinge, then base hinge) ensured by the selection of torques and energies in the drive springs.

The sensor – the Langmuir Probe (LP) – is a 100 mm diameter sphere at the end of the ~100 mm long stub. The LP consists of two hemispheres (0.4 mm thick). A hollowed stiffening cone (also 0.4 mm thick) is tightened to both hemispheres in place of their contact to provide high probe stiffness. To reduce the sphere's mass, the central coupler is in the form of a hollowed stiffening cone. The whole LP structure is made of titanium grade 5 alloy, and the external surface is covered with sputtered TiAlN coating (see Fig. 49). From an electrical point of view, the sphere and the stub are insulated from each other. Inside the sphere, there are custom-made and qualified purposely for this mission electric RC components. The resistor consists of a ceramic washer with resistive paths, while the capacitance is provided by an additional layer of conductive sleeve on the cable next to the resistor (also seen in the Fig. 49). The LP is mounted at the end of the deployable boom enabling it to extend from the spacecraft body. A total of four LP booms are extended from the S/C body in different directions.

### 4.2.9 LP-PWI Preamplifiers

The purposes of the LP-PWI Preamplifiers are to support plasma density and E-field measurements as well as active mutual impedance measurements (MIME). The preamplifier contains switches and amplifiers for the density and E-field modes. A block diagram is shown in Fig. 50. The preamplifier housing (see Fig. 31) is made of aluminium with an added Tantalum plate for radiation protection.
<figure><img src="image_53.png" /><figcaption>**Fig. 49** (Top) Langmuir probe assembly. (Bottom, left) The Langmuir Probe during assembly with exposed RC circuit elements. (Bottom, right) The details of RC elements</figcaption></figure>

### 4.2.10 Langmuir Probe (LP) Coating Design, Tests, and Considerations

The RPWI Langmuir probes and stubs are uniformly coated with a 0.6 µm layer of sputtered Ti₅₀Al₅₀ N with a detailed cleanliness procedure carried out at Linköping University. The choice was made after extensive testing of several different surface materials with different test-methods and will be described elsewhere. The RPWI Langmuir probe coatings were grown in a CemeCon AG CC800/9 magnetron sputter deposition system, using four TiAl cathodes, each operating at 6 kW in DC sputtering mode in a N₂/Ar atmosphere with a purity better than 99.999% (see Fig. 51). Prior to deposition, the probes and stubs are subject to a pre-treatment where the substrates are periodically immersed in a high-density Ar⁺ plasma jet to (i) effectively clean the surface from residual contaminants and (ii) activate the surface sites to provide better bonding to the TiAlN layer. Throughout the pre-treatment and the deposition, the probe parts are subject to a negative pulsed potential of -650 V at 240 kHz to achieve ion assisted film growth utilizing the magnetron plasma, while eliminating detrimental charge accumulation/discharge effects. The substrate temperature was kept at 475 °C (using resistive radiative heaters at 8 kW) to degas the surfaces during the pre-treatment and during deposition to provide sufficient mobility at the growing film surface, which is necessary to obtain dense and hard coatings with good adhesion. The probe hemispheres were
<figure><img src="image_54.png" /><figcaption>**Fig. 50** LP-PWI Preamplifier block diagram. If the relay control (blue dashed) is set to positive voltage the relays are set to the positions shown, if set to negative voltage the relays flip to the other position</figcaption></figure>

coated one by one assembled to a full sphere, allowing them to rotate freely on two concentric stainless-steel rings placed around the centre of the sputtering system (the rail system shown in Fig. 51). During the entire process, the rails rotate relative to each other causing the probe to roll in a quasi-random manner, giving the entire sphere's surface equal average exposure time to the deposition flux. This ensures a uniform coating and effective masking of all surfaces of the sphere's parts that are not to be coated. To avoid scratching of the pristine Ti-spheres during the pre-treatment stage, any (harder) TiAlN coating is removed from the (softer) steel rails, in-between each deposition. Other parts, such as the stubs were coated separately, and were rotated by a double planetary motion in the chamber during deposition.

During the development process, monitor samples of the same material were simultaneously coated and then tested for surface roughness (<300 nm), electrical work function (<0.03 eV rms), chemical composition (X-ray photoelectron spectroscopy, <0.1 atom %), surface reflectance (before and after high temperature annealing, optical properties, $\alpha/\epsilon < 1.7$), adhesion (tape testing in accordance with ISO 9211-4: 2006 (E), including on an irradiated sample, a sample subjected to thermal vacuum cycling, and a sample subjected to thermal shock) and repeatability across batches. Equivalent monitor samples from the flight depositions were characterised through the same surface reflectance and electrical work function measurements.

Prior to selection of surface coating material and deposition methods, several different candidate coating materials were developed at the Ångström Laboratory of Uppsala University (UU) and the Swedish Institute of Space Physics in Uppsala (IRF-U), and at the Centre for Nanoscale Materials (CNM) at Argonne National Laboratory (USA). A few of the test samples, deposited with Nitrogen doped Ultra Nano Crystalline Diamond (N-UNCD), are shown to the left in Fig. 52 and all candidate coating materials are listed in Table 12.

The electrical performance of these coatings and their sensitivity to contaminations were investigated during a one-week long test campaign at ONERA in Toulouse, using their large, 9 m³, IONospheric Atmosphere Simulator (JONAS) plasma chamber. The JONAS facility
<figure><img src="image_55.png" /><figcaption>**Fig. 51** Langmuir probes in flight configuration (top left), dis-assembled (two spares and four in-flight, top right), and one spherical probe on the rotating rail manipulator in the sputter deposition chamber</figcaption></figure>

simulates ionospheric conditions in LEO, with plasma densities in the $10^5–10^6$ cm$^{-3}$ range and electron and ion temperatures in the 0.1–0.2 eV range. As shown to the right in Fig. 52 twelve Langmuir probe surfaces (2 cm diameter Titanium plates with different coatings) were mounted on a carousel inside the plasma chamber on large aluminum plates, acting as guards. A resistor for probe cleaning, by heating, and a thermistor (PT1000) for temperature monitoring were installed on the backside of each probe. Thekarousel itself was driven by a stepper motor, which allowed to put the Langmuir probe under test directly in front of the plasma source. The electrical performance was evaluated from the current drawn by the Langmuir probes in response to the bias voltage, applied to the probe during the Langmuir probe sweep. Bias voltage sweeps from –5 V to +5 V (up) and from +5 V to –5 V (down) were used during the tests.

Contamination can only be estimated qualitatively by observing the hysteresis effect when performing double (up and down) voltage sweeps. Hysteresis indicates that the probe is contaminated, while no hysteresis means that the probe is clean. In the first attempts to
<figure><img src="image_56.png" /><figcaption>**Fig. 52** Left. Test Langmuir probes surfaces after being deposited with Nitrogen doped Ultra Nano Crystalline Diamond (N-UNCD) at Centre for Nanoscale Materials (CNM). Right: Carrousel with all test Langmuir probes inside the JONAS plasma chamber at ONERA. The plasma source is in the center of the chamber wall</figcaption></figure>

<table><caption>**Table 12** Test sample coating: Nitrogen doped Ultra Nano Crystalline Diamond (N-UNCD), monolayer graphene annealed on N-UNCD, Boron doped Nano Crystalline Diamond (B-NCD), manufactured using Chemical Vapor Deposition, sputtered Au, TiAlN, TiN, and baked TiN. Samples with different doping concentrations are not listed here for brevity</caption><thead><tr><td>Material</td><td>Thickness</td><td>Process</td><td>Provider</td></tr></thead><tbody><tr><td>N-UNCD</td><td>200 nm</td><td>Microwave plasma CVD</td><td>CNM</td></tr><tr><td>Graphene on N-UNCD</td><td>200 nm + monolayer</td><td>Annealing/Microwave plasma CVD</td><td>CNM</td></tr><tr><td>B-NCD</td><td>1 and 2 um</td><td>CVD</td><td>UU</td></tr><tr><td>Au</td><td>650 nm</td><td>Sputter</td><td>UU</td></tr><tr><td>TiAlN</td><td>650 nm</td><td>Sputter</td><td>UU</td></tr><tr><td>TiN</td><td>650 nm</td><td>Sputter</td><td>UU</td></tr><tr><td>TiN</td><td>650 nm</td><td>Baked</td><td>IRF-U</td></tr></tbody></table>

clean the probes, they were heated to about +150 °C, but this turned out to be a very time consuming and inefficient method. A much better method was found to be electron sputtering. As shown in Fig. 53 and Fig. 54, very efficient cleaning was achieved in only 1 1/2 hour, by setting the probe bias voltage to constant +32 V and letting the electrons sputter the probes clean.

The best electrical properties were shown for a 200 nm Graphene monolayer. However, the energetic oxygen radical environment near the icy moons of Jupiter may easily react with a Graphene layer. Instead, the second-best coating material was selected, i.e., sputtered TiAlN. Another consideration is that while it is comparably easy to deposit smooth surface coatings on small flat samples, this is not straight-forward for the large 10 cm diameter spherical Langmuir probes. The sputtering chamber facility at Linköping University facilitated this. The heritage from our previous development of sputtered TiAlN coating for the MEFISTO instrument onboard BepiColombo (Blomberg et al. 2006a,b) was also an important factor during the final selection process. Furthermore, thanks to the good results of probe cleaning with electron sputtering at ONERA, this method has been implemented for probe cleaning in in-flight. During the inner cruise phase, probe cleaning operations at +80 V for several days will be performed at least twice a year before payload checkouts and planetary gravity assist maneuvers.
<figure><img src="image_57.png" /><figcaption>**Fig. 53** Langmuir probe sweeps performed on 23 October 2015 at ONERA before probe cleaning by electron sputtering</figcaption></figure>

When searching for long term durable conductive surface coatings for the Langmuir probes for the Cassini RPWS-LP instrument in the 1990 s, titanium nitride was identified as a suitable candidate due to its high mechanical durability and chemical inertness. An extreme degree of adhesion was achieved by using a process of “baking”, i.e., conversion of the upper layers of a Ti sample to TiN by immersion in a nitrogen atmosphere at high temperature. Laboratory tests verified the general conclusions but showed that the probe would become very hot when passing Venus (Wahlström et al. 1992; Veszelei and Veszelei 1993).

During its lifetime, Cassini saw as wide a range of plasma conditions as JUICE will do, ranging from the very dense ionospheric plasmas during the Titan flybys and (even more) the end-of-mission orbits into Saturn's own ionosphere to the low-density regions of the Kronian magnetotail. The plasma density derived from RPWS-LP measurements, either by direct evaluation of probe bias sweeps or by a proxy method using the observed spacecraft potential, agrees very well with independent estimates using wave methods or particle integration (Wahlund et al. 2005, 2009, 2017; Morooka et al. 2009; Edberg et al. 2010, 2011, 2013; Holmberg et al. 2012, 2017, 2021). We consider the successful Cassini RPWS-LP as validating the use of a nitride coating for a Langmuir probe in conditions relevant to JUICE.

Two reasonable analogues for the RPWI electric field measurements are provided by Rosetta and Solar Orbiter. On Rosetta, RPC-LAP included two Langmuir probes, separated by 5 m that has been used in electric field mode, either with application of a bias current
<figure><img src="image_58.png" /><figcaption>**Fig. 54** Langmuir probe sweeps performed on 23 October 2015 at ONERA after probe cleaning by electron sputtering</figcaption></figure>

or as floating probes (Eriksson et al. 2007, 2017; Odelstad et al. 2017). The electric field mode data were calibrated to particle measurements for monitoring the spacecraft potential (Odelstad et al. 2017) and has been used for studies of lower hybrid and ion acoustic waves (Karlsson et al. 2017; André et al. 2017; Gunell et al. 2017a,b). The Solar Orbiter RPW instrument includes three antennas, which has been used with a bias current as low frequency electric field probes with effective baselines of 7 m (comparable to the JUICE LPs, see Table 5) in two directions. The electric field measurements could be calibrated and verified by comparison to magnetic field and plasma drift measurements (Steinvall et al. 2021) while the spacecraft potential is used for studying plasma density variations (Khotyaintsev et al. 2021).

For the MEFISTO instrument on the BepiColombo magnetospheric orbiter (MMO), use of TiN, as on Cassini and Rosetta, was not possible due to the excessive equilibrium temperature at Mercury. A study for finding a thermally acceptable surface with the TiN durability resulted in identifying sputtered TiAlN as a suitable coating (Brogren et al. 2000; Larsson and Wahlund 2004; Blomberg et al. 2006a,b). Application by sputtering provided the additional advantage of a smoother surface, which is easier to keep clean, as well as a more controlled and repeatable process. Note that the mechanical durability is more than sufficient for space needs also for nitriding by sputtering, with commercial use including the hardening of cutting surfaces (Chauhan and Rawal 2014).
### 4.2.11 SCM

Figure 55 shows the SCM flight unit and its PCB which includes the ASIC pre-amplifier. Each SCM sensor is made of a high permeability rectangular nanocrystalline ferromagnetic core (VP800 from VaccumSchmeltze) allowing high amplification at low temperature. The ferromagnetic core is inserted into a mandrel (made with PEEK GF30). Two high turn number copper wires are coiled around this mandrel, the first one to collect the flux into the ferromagnetic core and the second one for the feedback and calibration signal. The so obtained sensor is surrounded by an electrostatic shielding and inserted into a protection tube. The sensor is filled with a low-density potting material (Mapsil 213-B) to ensure mechanical vibration stiffness.

The voltage across the winding is amplified by a dedicated ASIC two-stages low noise preamplifier (see Fig. 55). Since this sensor exhibits a natural resonance, the first stage output voltage is used to feedback the secondary coil magnetically coupled to the primary one through the ferromagnetic core, allowing to flatten the transfer function response without any noise degradation. The ASIC preamplifier mounted on a thin PCB has been inserted into the mechanical structure. Three sensors are mandatory to retrieve the magnetic field vector. They are maintained orthogonally thanks to a dedicated mechanical structure. This mechanical structure is attached to the MAG-boom. The boom is shared with fluxgate magnetometers positioned at a distance such that EMC disturbances from the spacecraft as well as the fluxgates are minimized. The tri-axis antenna is wrapped with MLI to filter temperature variation and to maintain coldest temperature within an acceptable operational range (>77 °K and <150 °C).

SCM low noise and low power ASIC preamplifier is designed in AMS CMOS 0.35 µm technology. The amplifier is supplied through a voltage regulator based on bandgap circuit, which has been implemented to guarantee regulated voltage stability over a wide temperature range [-200 °C; +100 °C] while increasing supply rejection. The first stage is optimized to get low noise while the next stage provides the required gain to adjust the signal to the 14 bits digitization provided by LF receiver (see Sect. 4.2.6) and first order low-pass filtering (20 kHz). A calibration signal, connected to the ASIC preamplifier is provided by LF receiver to check the transfer function over temperature and time in flight. The calibration signal varies from few Hz up to 20 kHz, with at least one frequency per decade and duration of each sine is higher than 100 ms. Calibration will be done a couple of times per orbit in burst mode. The ASIC has been tested at temperature as low as 77 K and proved radiation ability higher than 400 kRad|Si] at low dose rate. As the transfer function of SCM may varies smoothly with temperature and aging, an internal calibration can be performed in flight when high precision data are requested.

### 4.2.12 RWI Antenna System

RWI consists of three pairs of mutually orthogonal tubular booms (called SDAs, Single Dipole Antennas) assembled with an electronic preamplifier box and located far out (8.6 m) of the JUICE S/C on the last segment of the MAG boom (Fig. 56; Grygorczuk et al. 2023). When stored, the tubular booms possess potential energy that actuates their deployment and needs to be additionally damped by a patented miniaturized oscillatory damper inside the storage reel. RWI has a mass of 2.2 kg and deploys to a relatively large distance of 2.5 m (tip-to-tip). During the launch, the antenna reels are held by locking arms secured by a Vectran string and is released in flight via a thermal knife principle (like LP-PWI).

All three dipoles are directly fixed to their common electronics box (called the RWI Box, Fig. 57) with a thickness of 3 mm, which houses the three preamplifier PCBs, each assigned
<figure><img src="image_59.png" /><figcaption>**Fig. 55** Top: the SCM flight unit mounted on its mechanical test interface plate. Bottom: the SCM PCB including the ASIC low noise pre-amplifier</figcaption></figure>

to one of the dipoles. Since the assembly on the MAG Boom is exposed directly to the space, the chassis components constitute thermal (together with two additional MLI blankets) and radiation protection for the electronics.

As mentioned above, the functional principle of the SDA is based on a tubular boom mechanism. The tubular boom strip is stored on a reel in the stowed configuration. When deployed, it forms a cylindrical tube with a diameter of c.a. 10 mm of a given length. The unquestionable advantage of the implemented solution is the lack of any motor drive and design simplicity. The deployment is based on energy accumulated in winded tape and its self-release during the transformation of the flat input profile to the original round one (Fig. 58). Notably, the selected material for the tubular booms is the Berrylium bronze alloy, which is non-magnetic (a strict requirement due to the proximity of the MAG boom experiment) and possesses unique strength properties, allowing for forming the tubes in a patented process. To meet the maximum allowable temperatures of the tubes, they are covered with sputtered DLC coating qualified for the mission and provide the necessary emissivity to absorptivity ratio.
<figure><img src="image_60.png" /><figcaption>**Fig. 56** (Left) Visualization of RWI dipole system on MAG Boom in stowed configuration. (Right) the actual Flight model of RWI antenna in stowed configuration before shipment to Airbus</figcaption></figure>

<figure><img src="image_61.png" /><figcaption>**Fig. 57** Visualization of RWI chassis depicting details of its interior (three of the walls are transparent)</figcaption></figure>

### 4.2.13 RWI Preamplifiers

A block diagram of the RWI preamplifier is shown in Fig. 59. The whole assembly is found in Figs. 31 and 56. RWI preamp consists of three identical differential amplifiers connected to U, V, and W SDA dipole antennas, respectively. At the input, signal clipping diodes are mounted at each amplifier input to mitigate the possibility of damage due to electric discharges. In parallel, the resistor of 1 Mohm connects between the antenna line to the ground for the leak of charging.

Those amplifiers have high raw gain of ~10 dB in 100 kHz – 25 MHz with the low noise floor of ~10 nV/Hz¹/². To keep high efficiency coupling with the SDA, the design aims the low base capacity, which achieves ~25 pF including the amp input capacity itself, the wiring capacity between the antenna to the preamplifier input, and the stray capacity. The output signals are transferred to the HFR via the long HF-RWI harness along the MAG Boom with the length of 17 m. Although we use low-loss coaxial harness for the signal line, its loss becomes –0.3 ~ –3.0 dB in 100 kHz – 25 MHz and the phase difference between U, V, and W, are also distorted by this long harness.
<figure><img src="image_62.png" /><figcaption>**Fig. 58** Final tubular boom during rolling on storage reel</figcaption></figure>

<figure><img src="image_63.png" /><figcaption>**Fig. 59** RWI antenna preamplifier</figcaption></figure>

The most important task for the JENRAGE experiment is the first achievement of high-precision polarization and the direction of arrival (DOA) measurements of the Jovian radio emissions. Those are disturbed by circuit characteristics (e.g., the RWI preamplifier characteristics, long RWI-HF harness, and the HFR). Including them, the practical electric field

<figure><img src="image_64.png" /></figure>
sensitivity will be determined with the antenna. Unfortunately, the antenna length, 2.5 m tip-to-tip, is shorter than previous ones which visited the Jovian system like Voyager, Ulysses, Galileo, and Cassini. The reduced sensitivity by the short antenna with the expected capacity of <10 pF and the effective length of <1.0 m will be calibrated during the cruise and flyby observations, which utilizes natural radio sources like solar radio bursts in all frequency ranges and the terrestrial AKR below 1 MHz. In addition, HF also provides a calibration (CAL) signal to the RWI preamplifiers, to check the effects of temperature changes and degradations caused by radiation. The results will be summarized in a forthcoming paper on the JENRAGE calibration after the first Earth flyby.

As shown in Fig. 59, the RWI preamplifier has three preamplifier PCBs and one common PCB connected by flexible harness. Those are located inside the RWI chassis (Al, 3-mm thickness), and the active parts on each PCB are also covered by its own shield (Ta, 1.3-mm thickness) for protection against the harsh radiation in the Jovian environment. In the pre-launch analyses, the expected TID would be ~100 krad. To endure this level, all the active components used by the RWI preamplifiers are specified by the manufacturer to withstand 300 kRad of TID.

Although we established the preamp will work for -180 °C ~ +90 °C, the gain is gradually reduced below -140 °C. To keep the preamplifier temperature even in the cold Jovian environment, the RWI preamp PCBs are thermally decoupled from the RWI chassis, by the PEEK supporters etc. By this effect, during the turn-on with ~500 mW power dissipation of +8.5 V, the RWI preamplifier temperature was kept as ~ 20 °C from the RWI chassis (i.e., ~RWI preamplifier temperature is ~-140 °C when RWI-chassis temperature is -160 °C). As a backup, RWI PCB can also activate an internal heater which provides additional 100 mW on the PCB next to the active parts. On the other hand, in the higher temperature environment like the flyby at Venus, this temperature difference reduces to ~5 °C (i.e., ~75 °C when RWI-chassis temperature is +70 °C), because higher radiation coupling between the PCBs and the chassis wall can be.

However, it means that the RWI preamp could be in very low temperature as the RWI chassis when its power is off. The gain becomes less when PCB temperature is lower than -140 °C, and it takes several 10 s min to reach the operational temperature and thermal equilibrium after the turn on. To avoid such unnecessary thermal cycling and for the emergencies, the S/C provides two survival heaters (nominal and redundant) attached on the outside of the RWI chassis. Once the S/C is beyond Mars and reaches the Jupiter orbit, when RWI is powered off, this heater can be activated by the S/C system (28 V) and continuously heat the RWI chassis with 300 mW. It can keep the RWI chassis at a reasonable temperature (> -160 °C) around the Jovian environment. This heater power is supplied from the System, but this path is through the HFR with a relay system. When this heater is off, the relay connects the survival heater lines to the RPWI EBOX chassis ground, to reduce the possible noise from the system power supply. This design is equivalent to the RWI deployment lines.

## 4.3 RPWI Mass, Power, Telemetry

### 4.3.1 Mass (Table 13)

* The orientation bracket for RWI is **not** included, with measured mass of 322.3 g.

* The MLI mass for RWI and SCM (which reside on the MAG boom) is included.
<table><caption>**Table 13** RPWI sub-unit mass</caption><thead><tr><th>Unit ((P)FM)</th><th>Measured [g]</th></tr></thead><tbody><tr><td>EBOX (2 mm structure + 6 mm rad shield + internal PCBs)</td><td>8518</td></tr><tr><td>LP-PWI (booms+sensors)</td><td>4973</td></tr><tr><td>LP-PWI (preamp box + washers + stand-offs)</td><td>944</td></tr><tr><td>SCM (sensors+amps+MLI)</td><td>631</td></tr><tr><td>RWI (antennas+amps+MLI)</td><td>1797</td></tr><tr><td><strong>RPWI total mass (with shielding)</strong></td><td><strong>16,863</strong></td></tr><tr><td><strong>Margin[%] (allocated 19.1 kg incl. shielding)</strong></td><td><strong>13.3%</strong></td></tr></tbody></table>

<table><caption>**Table 14** Subsystem representative maximum power usage when active. The numbers will vary with used operation modes for each sub-system. The modes in the top row are RPWI OFF (OFF), RPWI start up (Init), RPWI Standby and Safe modes, and RPWI max power science mode. Nominally the RPWI power consumption during science sampling will be around 12 W and significantly less than 21.8 W</caption><thead><tr><th>Power modes [mW]</th><th>OFF</th><th>Init</th><th>Standby</th><th>Safe</th><th>Science (max)</th></tr></thead><tbody><tr><td>LP-PWI sensors</td><td>0</td><td>0</td><td>0</td><td>0</td><td>528</td></tr><tr><td>SCM sensors</td><td>0</td><td>0</td><td>0</td><td>0</td><td>279</td></tr><tr><td>RWI sensors</td><td>0</td><td>0</td><td>0</td><td>0</td><td>556</td></tr><tr><td>MIME drivers</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4</td></tr><tr><td>LP-MIME</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2987</td></tr><tr><td>LFR</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2658</td></tr><tr><td>HFR</td><td>0</td><td>0</td><td>0</td><td>0</td><td>7058</td></tr><tr><td>DPU</td><td>0</td><td>1883</td><td>1718</td><td>1718</td><td>1883</td></tr><tr><td>LVPS 77% eff. + 1100mW</td><td></td><td>1100</td><td>1100</td><td>1100</td><td>1100</td></tr><tr><td>EBOX (dissipated)</td><td>0</td><td>3547</td><td>3333</td><td>3333</td><td>20477</td></tr><tr><td><strong>Total Power (Nom)</strong></td><td><strong>0</strong></td><td><strong>3547</strong></td><td><strong>3333</strong></td><td><strong>3333</strong></td><td><strong>21839</strong></td></tr></tbody></table>

### 4.3.2 Power (Table 14)

### 4.3.3 Telemetry

The TM rate and Power will depend on the used operation mode of RPWI (there are many). Nominally the TM rate varies between 2.3 kbps–65.7 kbps with a power of nominal power of 13.9 W. If the HF measures in radio burst or PSSR modes, then the TM rate and power may increase up to 1.6 Mbps and 21.8 W. RPWI also have a special low TM mode for downlink and spacecraft eclipse cases. See Sect. 6 for telemetry details of different operation modes.
## RPWI SOFTWARE OVERVIEW

<figure><img src="image_65.png" /><figcaption>Fig. 60 Overview of the RPWI DPU software</figcaption></figure>

# 5 Flight Software

## 5.1 General Design Goals & Architecture

The RPWI flight software runs on the DPU, which has a dual core. Other flight software (VHDL for FPGAs) that run on the different subsystems is called firmware, as it is tightly linked to the hardware. The firmware and special receiver related application software (ASW) is described in Sects. 5.4 (LP), 5.6 (LF), and 5.8 (HF). The RPWI flight software
runs on a LEON3FT processor at a clock speed of 50 MHz. To handle the load of the most intensive science modes, both cores (referred to as Core 0 and Core 1) are utilised. Most core functionality, together with LF and LP DPU Software run on Core 0. Meanwhile, HF and MIME DPU Software run on Core 1, together with their required drivers and those required for inter-core communication. No work-sharing is done between the cores. An overview of the RPWI software is displayed in Fig. 60.

The software is built on top of the real-time operating system (RTOS) RTEMS. The software is written in the C programming language, using assembler strictly only when needed for small segments of code. It uses an event-driven task switching model to enable high priority tasks to interrupt lower priority tasks without taking away execution time when there is no high priority event to service. Non-blocking mutex locks are used to synchronise access to shared resources from multiple tasks. The boot loader is not using RTOS. The DPU software has several interfaces to the hardware. There are four to five internal data input links, interrupt signals and two space wire output links. Memory mapped I/O and interrupts will be used to communicate with the internal data links, DMA tables and interrupts will be used to communicate with the space wire links. We divide the software into logical blocks as follows (note that the blocks do overlap):

* Boot loader

* Overall control system

* Operational modes, science, and maintenance etc.

* Sequencing and duty cycling

* Kicking watchdog

* Etc...

* Receiving telemetry

* Parsing telecommands

* Sending telemetry

* Data pipelines

* Packaging of telemetry

* Science algorithms

* Spacecraft services

* Memory patching

* Memory dumping

* Event reporting

* Critical limits checking

* Etc...

* Housekeeping generation and transmission

* Time stamping and time handling

* Error handling software

These blocks are mapped to different PUS services described at the end of this Section. They also map to different tasks in the RTEMS task model. Task priorities are assigned in this order (TC, LVPS, FDIR and sequencer tasks only run on Core 0) and no two tasks share the same priority value:

1. Operational task – handle high priority telecommands, DPU hardware control

2. TC task – handle medium and low priority telecommands

3. LVPS tasks – control LVPS, handle LVPS telemetry

4. FDIR task – detect out of limit sensor or status values, perform appropriate actions

5. Sequencer task – run the operational sequencer

6. Subunit hardware tasks – control sub-experiment hardware
DPU Software data pipelines

<figure><img src="image_66.png" /></figure>

* Example block processing => FFT, Example Stream => Digital filtering.

* Max input rate: 100KS/s to 1MS/s 16bit wide

* Above buffer memory estimates above assumes 4 to 8 MB of RAM memory.

* A balance should be achieved between centralized processing (DPU) and localized processing (HF,MF,LF).

<caption>Fig. 61 DPU software data pipelines</caption>

7. Data pipeline tasks – process, compress and encode sub-experiment data, see below

Main task – kick watchdog, send housekeeping, perform routine maintenance

The core component of the software is the data pipelines describing the dataflow. The data pipelines in Fig. 61 describe two different examples of stream processing and block processing; both of which are used in the RPWI software. Block processing is used when all data need to be present before the processing starts, while stream processing will be used when you can start immediately. In both examples above data enters from the top coming from the instruments and exiting at the bottom to the spacecraft. The numbers 1, 2, 3 and 4 describe double buffers, where the arrows represent data flows and the colours red and blue represent different phases in time, blue could be the present state and red the next cycling back to blue and so on. The Pulse Per Second (PPS) represents a pulse generated each second and defines the highest rate a single pipeline can create output data packets.

Each of the sub-experiments (MIME, JENRAGE, GANDALF, SAMWISE) have their own pipeline consisting of one or more branches. Each branch has three stages: processing, compression and encoding. The processing stage is responsible for processing and packaging raw science data to produce the science products defined by the current instrument configuration. This includes the compression stage, after the processing part of each unit, responsible for compressing the science products for efficient storage and transfer. The encoding stage is responsible for preparing the compressed science products to be sent over SpaceWire by splitting up large packages and adding AUX headers.
Each pipeline branch stage is represented as its own task. In most cases, later pipeline stage tasks are given higher priority than their previous stages to ensure data flow even under a heavy load on the processing stage. However, MIME, which samples a large amount of data but only under a very short period, inverts this order to allow a higher acquisition rate than the maximum processing throughput by letting data buffer up in the pipeline and then process it later. Since no two tasks are assigned the same priority under our task model, LP tasks are prioritised higher than LF tasks and HF tasks are prioritised higher than MIME tasks.

The produced science data is divided into two categories: rich data and survey data. Rich data consists of high-resolution data which is produced at a greater rate than can be downloaded to Earth. Survey data generally consists of low-resolution data created through filtering and down-sampling of rich data to reach a data rate small enough to allow downloading all of it.

For the download of rich data, there exists two strategies: triggers and selective downlink. Triggers are programmed conditions for selecting which rich data to keep or discard based on what is detected in the science data. By limiting the number of times, a trigger can happen within a period, the amount of rich data sent to Earth can be kept within the bandwidth limits of the downlink. Selective downlink, on the other hand, is the practice of saving all rich data to the spacecraft mass memory and then select from Earth which time periods to download based on the information in the survey data. During the cruise phase of the mission close to Earth, all data (including rich data) will be downlinked without the need of Selective downlink.

The primary instrument control mechanism within the software is the sequencer. The mission timeline is another control mechanism. The sequencer provides 20 sequence tables, with each table capable of holding a sequence up to 64 lines long. Each PPS, the sequencer reads the current line in the current sequence table and executes it. Every line in the table describes certain actions the flight software will take when that line is executed, most notably selecting when to switch sub-instrument configurations and which configurations to switch to. Each line also describes which line to execute next and includes an optional repetition counter, thereby making it possible to create both finite and infinite loops within the sequence. If the sequencer reaches the end of the sequence table, it will restart from the top.

Each sub-instrument has 16 configuration sets containing all parameters required to define its operation, such as power settings, sweep tables and decimation values, as well as any other values which cannot be inferred at runtime, such as number of pipeline branches and their buffer sizes. Each configuration set is double buffered to allow updating a configuration while it is running.

For communication with the spacecraft and Earth, the flight software provides the following standard Packet Utilisation Standard (PUS) services for telecommand and telemetry handling:

* Service 1 – request verification

* Service 3 – housekeeping

* Service 5 – event reporting

* Service 6 – memory management

* Service 8 – function management

* Service 9 – time management

* Service 17 – test

In addition, the software provides the following mission-specific services:

* Service 145 – updates from J-MAG and reaction wheels
* Service 146 – enable/disable remote memory access protocol (RMAP) and destination logical addresses

* Service 204 – science data reporting

* Service 205 – telecommand echoing

## 5.2 DPU Application S/W

Each RPWI experiment and compression has application software (ASW) installed in the DPU (see relevant Sections below).

## 5.3 Compression

Data compression aims to represent the output from a sensor or onboard process as compactly as possible without loss of significant information. Compression methods may be classed either as ‘loss-less’ in which the original digital data may be recovered exactly, or ‘lossy’ which aims to preserve significant information, but does not recover exactly the original data, in effect reducing the precision of the measurements. With loss-less compression, the resulting data volume depends on the characteristics of the data, and no amount of compression can be guaranteed. However, on typical data a 2:1 ratio or better can often be achieved. When the available data storage (or telemetry bandwidth) is not sufficient to contain the compressed data, the options are either to store (or transmit) less samples, or to represent the samples less precisely.

The compression implemented for RPWI is normally loss-less, with an option to reduce precision to achieve a specified data volume by discarding the least significant bits. The compression is based on CCSDS standard 121.0-B-3 (CCSDS 2020), which comprises:

* A pre-processor which applies a reversible function to reduces the information content (numerical entropy) of the data as much as possible.

* An entropy coder which codes that information in the smallest number of bits.

The choice of pre-processor is the key to achieving good compression. RPWI employ both the unit delay predictor, where each sample is replaced by the difference between its value and that of the previous sample using modular arithmetic, and Linear Predictive Coding (LPC), where the difference from a prediction based on a linear combination of N previous samples is made. In the RPWI implementation LPC is applied to a single data component or a single spectrum using contiguous previous samples. Whilst it is in principle possible to use multiple components or spectra, thus exploiting inter-channel correlations, tests showed that for a given number of prediction coefficients the single channel implementation gave the best results. It is also considerably faster as the Levinson–Durbin method of matrix inversion may be used to calculate the coefficients, rather than Gaussian Elimination.

The standard specifies that the Rice algorithm (Rice et al. 1993) shall be used as the entropy coder, with exceptions including no compression and run length encoding when these result in a smaller data volume. This is an optimum way to encode data with a geometric distribution, which the pre-processor aims to achieve. The Rice algorithm has a single ‘tuning’ parameter *k* which is chosen to achieve the smallest data volume. The standard specifies this will be done by trying each value in turn, which is computationally expensive. Instead, the RPWI implementation uses a method described by Kiely (2004) based on the mean value ($\mu$) of the input ($k = \lfloor \log_2(\mu + 0.382) \rfloor$). In our tests Kiely’s method selects the optimum value in 95% of cases with the remainder being border line cases unlikely to affect compression efficiency if an adjacent value were used.

Data compression for RPWI has two important requirements:
* The processing time must have a well-defined upper bound so we can be sure that the data will be processed in the time available.

* Spacecraft telemetry systems are not 100% reliable. Loss of data can occur during marginal link conditions. The data must therefore be processed in self-contained blocks, such that no other data are required to perform the decompression.

Both pre-processor implementations are primarily intended for application to linear numerical representations of physical quantities such as a voltage applied to an analogue to digital converter. Special considerations are needed for other source data formats. For RPWI these include the raw output data from the receivers' FPGAs, and floating-point data produced in the DPU tasks.

FPGA data may be processed simply as an array of bytes using the 'unit delay' pre-processor. Each byte within the data frame is processed as a separate component, with differences taken with respect to the same byte position in the previous frame. The use of modular arithmetic means this works efficiently even if the bytes are part of a larger numerical quantity.

Floating point data is handled by noting that the IEEE floating point format used (including the mini-float variants) when cast to an integer is effectively a piece wise approximation to the logarithm of the original data. In general, the integer representation shows three distinct ranges corresponding to negative, zero, and positive float values. These ranges need to be translated so they appear adjacent when applied to the compression (to avoid large difference values when transitioning from one range to another).

## 5.4 LP Receiver DPU Software

The LP part of the DPU software is responsible for configuration and control of the LP receiver hardware, as well as handling and processing data produced by the same. LP software is also responsible for calculating the spacecraft potential from electrical field data and sending it to the JUICE on-board computer for further distribution to other instruments. LP software is incompatible with MIME DPU software and must not interact with the LP receiver hardware while MIME software is active.

The core component of the LP configuration is the LP sequencer table. Each table row consists of a command with two arguments. The commands can select what LP software sub-mode to run, write a value directly to a LP receiver hardware register, generate new sweep tables, or tell LP software to wait for a set amount of time or for certain triggers. The LP sequencer table can contain at most 50 commands, which are executed when LP is enabled via the operational sequencer or via telecommand. Commands are executed one after another in order, and LP software will infer most of its behaviour from the written hardware register values. This grants fine control over the LP software and receiver hardware, but care must be taken to ensure no timing or order invariants are violated.

While LP allows a wide range of possible configurations, default implementations focus on a few specific categories of data products:

1. DE763 & DE24 – This category features time series of plasma density or electrical field data measured at a rate of 763 samples per second. This rich data product is passed through a low pass FIR filter and decimated to produce a parallel survey data product of 23.8 samples per second. A configuration flag allows for disabling the rich data product during periods of especially strict bandwidth constraints.

2. Voltage sweeps with hardware or software decimation – This category features plasma density sweeps, either between ±10 V or ±80 V, and optionally with some probes configured for measuring electrical field or plasma density with a fixed bias. A configuration
<figure><img src="image_67.png" /><figcaption>Fig. 62 MIME basic operations philosophy</figcaption></figure>

flag allows running either single or double sweeps, where the latter runs the two available sweep tables back-to-back. Due to hardware limitations, the LP receiver hardware will discard an equal number of samples to remove the step response regardless of whether the channel is sweeping or not. To counteract this, a configuration value can enable LP software to perform this decimation only the sweeping channels.

3. E694k – This category features electrical field snapshots, typically containing 16,384 samples, with a sample rate of 694,000 samples per second. The data follows a special raw data format where each sample has a lower resolution (14 bits instead of 21) and carries a minimal number of metadata, meaning this data product must be timestamped by LP software using the DPU clock instead of by LP hardware.

4. D49k – This category features plasma density sweeps, typically containing 32,768 samples, measured with a sample rate of roughly 48,800 samples per second.

5. Frequency sweeps – This category features complex electrical field data measured with the mixer active and centre frequencies taken from an automatically generated sweep table. Each step in the table shifts the centre frequency by 75% of the sample frequency to create overlapping bins suitable for FFT analysis. The full sweep typically covers the bandwidth 0–1.54 MHz.

## 5.5 MIME DPU Software

The main tasks of the MIME DPU software are (see also Fig. 62):

* To configure the instrument. MIME has two fundamental antenna configurations. Either the four Langmuir probes are used for emission/reception (LP/LP), or the Langmuir probes are used for emission and the RWI antennae are used for reception (LP/RWI).
* To generate a sinusoidal signal at a frequency determined from a frequency sweep table. This signal is then applied to one or two Langmuir probes for both configurations (LP/LP and LP/RWI).

* To synchronously analyse the received signal, which is carried out in the DPU in two different ways depending on the instrument configuration (LP/LP or LP/RWI). The products of the analysis are the amplitude and the phase spectra of the electric field.

MIME performs two different types of measurement: passive and active. In active measurements, MIME synchronously performs signal transmission and reception while in passive measurements, there is no transmission and only a reference signal is acquired. On one hand, active measurement relies on an on-board frequency table to construct the spectrum by successively transmitting at different frequencies and analysing the received signal around these frequencies. On the other hand, passive measurement is carried out over the entire frequency range of interest by taking samples through a filter all along the frequency span. An FFT with amplitude averaging is then applied to produce the passive spectrum.

The MIME ASW has four science modes, which all have a maximum active duration of 2 seconds:

* **Wide sweep mode:**

This mode performs sweeps in the entire low and high-frequency bandwidth with the aim to measure the plasma frequency $f_{pe}$ with a fixed resolution. This mode produces two passive and two active spectra: 1 passive and 1 active sweep is produced from 3 kHz to 1.5 MHz in LP-LP configuration, and 1 passive and 1 active sweep is produced from 80 kHz to 3 MHz in LP-RWI configuration. The mode only uses 1 channel in LP-LP mode and 1 channel in LP-RWI mode.

* **Nominal Sweep mode:**

This mode performs sweeps on a selected frequency bandwidth with the aim to measure the plasma frequency $f_{pe}$ with a chosen resolution. The mode has 8 sub-modes that can use either 1, 2 or 3 reception channels (dipoles). Each sub-mode uses a defined number of channels (dipoles), performs a defined number of sweeps, and generates a defined number of frequencies. The configuration of dipoles is given by hardware switch positions.

In addition, there are two additional sub-modes. A relaxation mode, which performs a mutual impedance measurement, waiting for the plasma to “relax” and performing a measurement on the residual amplitude. It only uses the LP/LP configuration. The second sub-mode is the slow mode, usable when the amount of TM available for MIME is low. It consists of a nominal passive sweep and an active sweep with a reduced number of frequencies.

* **Tracking mode:**

This mode determines local density gradients by following the short time-scale evolution of the plasma frequency $f_{pe}$. This mode carries out a measurement on either LP-LP or LP-RWI. A passive sweep is performed followed by an active sweep on the entire corresponding frequency span. A search algorithm is then run on the data to determine the frequency of the maximum amplitude in the spectrum. A series of active sweeps are then successively performed over a narrower frequency band encompassing that value.

* **B-field mode:**

This mode determines the magnitude of the static magnetic field. It is an experimental technological mode. This mode consists of performing a linear sweep in the frequency
range of 3 kHz to 100 kHz, performing computation on the data measured to determine the electron gyro frequency and performing other sweeps around the electron gyro frequency harmonics. The second sweeps will use a specific hardware mode called "wide noise" that offers the possibility to emit on a wide range of frequencies. As a result, the obtained signal corresponds to a large spectrum with a resolution proportional to the emission duration. In addition, as an extra functionality, this mode can also be used to measure the plasma frequency at high resolution within this frequency range. Indeed, the processing to obtain the gyro frequency and the plasma frequency is very similar so the functionalities implemented in this mode can be multipurpose.

The mutual impedance spectra reflect the characteristics of the equivalent electric circuit (composed by the transmission and reception devices and the surrounding plasma) as a function of the frequency and depending on the plasma local properties. They are then analysed on the ground to infer the main plasma response and, when possible, derive the electron density and the electron temperature.

## 5.6 LF Receiver DPU Software

The LF part of the RPWI application software takes care of configuration and control of the LF receiver as well as handling and processing of the raw data transmitted by the LF receiver to the DPU. This software layer is highly configurable and allows to adjust the set of components to be transmitted, snapshot length, frequency axis of the spectral products as well as details of the spectral processing and waveform snapshot triggering – an algorithm to automatically detect plasma waves and dust impacts in the LF data. The LF software is compatible with the sequencer cycle of RPWI but does not use this cycle to control the configuration of the hardware. Instead, the LF receiver is configured to a desired configuration on entering science mode and remains in the same configuration until powered off or until a new configuration is set by a telecommand.

The LF software handles the incoming data from the LF receiver in three parallel pipelines implemented in separate RTEMS tasks: one pipeline for the decimated waveform at 762.9 sps (DWF), one for spectral matrices (SM) and one for the full resolution waveform snapshots (WFS).

The following data products can be generated after post processing of LF data by the software.

Waveform data products:

* A continuous time series of magnetic field fluctuations (SCM) from E/D signals (LP) sampled at a rate of 762.9/2^N samples per second, where N is configurable between 0 and 5. For values of N > 0, the decimation of the raw DWF data is performed in software by an FIR filter of order 512.

* Waveform snapshots sampled at 762.9 samples per second. These snapshots of up to 16,384 samples per second are extracted from the DWF data stream.

* Snapshots of time series sampled at 48.8 kHz or 24.4 kHz of up to 262,144 samples per component. These snapshots are taken by the LF receiver periodically and if triggering is enabled (see below), the software selects which snapshot will be sent to the ground and which snapshots are discarded.

All the waveform products above are transmitted as 16-bit integer values and the number and configuration of field components can be chosen arbitrarily by a telecommand. For some
products, only the three SCM signals are typically selected, while for others a set of 7 (3 magnetic and 4 electric field and/or density) components is sent to the ground.

### Spectral data products:

* Averaged cross-spectral density matrices of selected components. These are averaged in the LFR board FPGA and the result is then further averaged in time in the software and compressed to an efficient form. An arbitrary frequency axis can be defined, typical configurations use a logarithmic frequency axis of up to 128 bins.

* Propagation and polarization parameters calculated on-board from spectral matrices. These include the intensity of the electric and magnetic field fluctuations, ellipticity, sense of polarization (left- or right-), degree of polarization (coherency), wave vector, and Poynting vector for a set of preselected frequency bands. This is a highly compressed product with minimum telemetry requirements. Two version of the product exist (BP1 which is effectively a more compressed version of the spectral matrix and requires 16 bytes per frequency bin and BP2 which contains the on-board calculated wave properties condensed into 4 bytes per frequency bin. Magnetic field vectors provided to RPWI on-board by the J-MAG instrument are used in the calculation of the wave parameters. They are used to transform the SCM data to field aligned coordinates before averaging and allow to evaluate projection of the Poynting vector to magnetic field direction. Due to the efficient form, these products can be generated at a high time resolution. The cadence of this data product is configurable from 250 ms to 30 seconds while its frequency axis is shared with the cross-spectral matrix data products, but can be reduced by summing together 2, 4 or 8 adjacent spectral bins.

### Statistical data, triggering and event detection:

The LF software also implements several internal algorithms for event detection and snapshot triggering. The baseline triggering algorithm operates on each WFS snapshot taken by LF receiver. The instrument can be configured to collect and process up to 1 snapshot of 16,384 samples per second, corresponding to a 33% duty cycle. If longer snapshots are configured, they must be taken less frequently not to exceed this duty cycle limit imposed by the required processing load on the RPWI CPU. The detection algorithm calculates peak amplitude, median absolute value, RMS amplitude as well as a number of sign changes ($Z_x$) for a selected component. The classification of the snapshot is then performed by comparing the ratio $R_{pm}$ of peak amplitude to median absolute value and the number of sign changes to predefined thresholds. Events can either be classified as waves for large $Z_x$ and small $R_{pm}$ or as dust impact spikes for the opposite case. An additional decision criterion is the RMS power in magnetic components; it is assumed that only plasma waves can have a significant magnetic component.

The triggering algorithm records the results of the processing of each snapshot and transmits characteristics such as a number of waves, dust impacts, peak and RMS amplitudes in the form of a short statistical data packet. The classification also assigns a quality factor to each snapshot and the highest quality snapshot is stored in a temporary buffer and transmitted to the spacecraft at the end of the RPWI sequence cycle. A second triggering algorithm based on spectral matrices and wave parameters is also implemented, but this only allows to detect waves and not dust.

## 5.7 S-WPIA

Software-type Wave-Particle Interaction Analyzer (S-WPIA) is a software function that can run in the DPU but is currently considered to be run on ground only. S-WPIA computes
physical quantities using wave electromagnetic fields and velocity vectors of plasma parti-
cles to measure the energy transfer between plasma waves and particles directly and quanti-
tatively (Katoh et al. 2017, 2018). The significance of WPIA has been demonstrated by re-
cent spacecraft observation in the terrestrial magnetosphere (Kitamura et al. 2018; Asamura
et al. 2021; Shoji et al. 2021). The prime target of S-WPIA in JUICE is ion cyclotron waves
(~1 Hz) and related wave-particle interactions occurring in the region close to Ganymede
and other Jovian satellites.

S-WPIA uses waveform of wave electromagnetic field sampled by GANDALF and/or
SAMWISE, and particle counts measured on-board by PEP/JDC and transferred on-board
by a link to RPWI. S-WPIA also uses the background magnetic field vector **B**₀ measured by
J-MAG. S-WPIA uses the wave and particle data sampled in the region of interest during the
same time interval. The in-flight S-WPIA computation significantly reduces the data volume
to be downlinked to the ground, but the computation can be carried out on ground as well as
all data is currently planned to be downlinked.

S-WPIA collects the wave and particle raw data sampled in the region of interest during
the same time interval. The raw data measured by PEP/JDC and J-MAG can be transferred
to RPWI through inter-instruments communication. PEP/JDC data consists of the number
of particles counts *C* as a function of energy (*K*), azimuth (*φ*), elevation (*α*), and mass-
per-charge (*m/q*) with a time-tag showing the timing of the measurement. S-WPIA collects
electromagnetic waveforms and the background magnetic field vectors measured simultane-
ously with the particle data and packs them into 1 data-unit. The stored high-resolution raw
data will be transferred to the ground for detailed analysis.

The variation of the kinetic energy *K* of a charged particle can be obtained by computing
the inner product of wave electric field *E* and velocity vector *v*ᵢ to obtain *W*ᵢ = *q*ᵢ *E* •
*v*ᵢ = *d*Kᵢ/dt. By accumulating *W* for particles detected during a certain time interval to
obtain *W*int = Σ *W*ᵢ, we obtain the amount of energy transferred between plasma waves and
particles.

S-WPIA uses *C* (*K*, *φ*, *α*, *m/q*) and electromagnetic waveform *E*(*t*) and *B*(*t*) to compute *W*<sub>int</sub> (*K*, *θ*, *ζ*, *m/q*), where *θ* is the pitch angle, *ζ* is the relative phase angle between wave magnetic field and particle velocity vector, *θ* and *ζ* are computed from *φ*, *α*, *B*, and *B*<sub>0</sub>. The number of particles *N* and the standard deviation *σ* of the computed *W*<sub>int</sub> are also obtained. We integrate the output matrices of S-WPIA, *W*<sub>int</sub>(*K*, *θ*, *ζ*, *m/q*), *N*(*K*, *θ*, *ζ*, *m/q*), and *σ* (*K*, *θ*, *ζ*, *m/q*), for *ζ* and/or *θ* to reduce the data size to be transferred to the ground in a later stage as well as to measure the energy exchange with the statistical significance. The S-WPIA output matrices indicate the region where strong wave-particle interaction occurs and can be referred to in selecting the full downlink of the stored high-resolution raw data.

## 5.8 HF Receiver DPU Software

The HF receiver DPU Software treats the command to, the housekeeping (HK) from, and
the telemetry from the HF receiver. The commands sent from the spacecraft are received by
the HF DPU software and sent to the HF receiver triggered by PPS pulse. Those are sent
to the HF FPGA and set the hardware and raw telemetry modes. The HK are taken from
the HF receiver and the DPU HF software itself. Those are sent to the spacecraft once per 1
second.

The HF receiver telemetry includes the whole properties of radio waves produced by
many different radio sources at Jovian polar region and atmosphere, the Jovian magneto-
sphere and the Io torus, and the vicinity of the icy moons, including Ganymede's magneto-
sphere (cf. Sects. 2.5, 3.14 and 3.15). Those data also contain the occulted, refracted, and
<table><caption>**Table 15** Maximum lengths of continuous wave form HFR</caption><thead><tr><th>Decimation</th><th>Data rate (−3 dB)</th><th>Effective bandwidth</th><th>Max data length [msec]<br>65,536 samples / data rate</th></tr></thead><tbody><tr><td>304</td><td>296 ksps</td><td>224 kHz</td><td>221</td></tr><tr><td>608</td><td>148 ksps</td><td>112 kHz</td><td>422</td></tr><tr><td>1216</td><td>74 ksps</td><td>56 kHz</td><td>885</td></tr><tr><td>2432</td><td>37 ksps</td><td>28 kHz</td><td>1771</td></tr></tbody></table>

reflected waves via the ionospheres, surfaces, and sub-surfaces of icy moons (cf. Sects. 2.5 and 3.3). The data stored in the spacecraft are transferred to the ground fully or partially after the selection. We summarize here the data flow, including the raw data transferred from the HF receiver, the processing in the DPU, and the produced data telemetries.

### 5.8.1 Raw Data Transferred from the HF Receiver

From the HF receiver, the DPU can receive the down-converted waveform at arbitral frequencies between 80 kHz–45 MHz, at stepped central frequencies. The data is taken based on ‘the sweep table’ stored in the DPU. The start of each frequency sweep is triggered at the timing of PPS pulse sent to the HF receiver.

The sweep table contains the list of central frequency steps and the number of down-converted waveform samples for each step. The number of the frequency step can be set as 1–512, and the number of samples in each frequency step is set as 1–65,536. The output waveform also depends on the decimation (Table 15). Those parameters can be flexibly selected with telemetry modes.

### 5.8.2 HF Data Telemetries Produced from the HF DPU Software

The raw data stream from the HF receiver is stored in the data buffer in the DPU with the size of 10 MB. The HF software reads this data and produces the telemetry which contains power, polarization, cross spectra information or waveforms. The processes include the averaging in the frequency and time regimes, the calculations of auto and cross correlations, and the rejection of noises and interferences generated by the spacecraft.

For the telemetry production, the HF software has the following sequence: (1) HF receiver FPGA setting, to set the sweep table, to set CAL ON/OFF, etc., (2) Software setting, to set the data processing mode, (3) Data acquisition from the HF receiver, (4) to process the data, and (5) to transfer the telemetry into the compress and encoding.

The following HF data telemetry modes currently exist, (1) Radio-Full mode, (2) Radio-Burst mode (rich/survey), (3) PSSR-1 mode (rich/survey), (4) PSSR-2 mode (rich/survey), and (5) PSSR-3 mode (rich/survey). In total, HF produces five major modes of telemetries plus a Test (RAW) mode which transfers the HF receiver raw I/Q waveforms directly. During the cruise phase, the implementation of the final HF operation modes will depend on the results from calibrations and the trial of artificial noise rejections.

#### (1) The ‘Radio-Full’ mode

Radio-full mode is used for long-term monitoring of radio waves, intended mostly for the Jovian orbiting phase to study the general variability of the magnetosphere. Down-converted I/Q waveforms is sent from the HF receiver, where the central frequency is swept once per sequence cycle (usually 30–600 s), with logarithmic 256 steps from 80 kHz to 45 MHz.
There exist several sub-modes; (a) power spectrum, 3 components, (b) spectral matrix, 9 components, (c) spectral matrix with polarization separation (linear, right- and left-handed), 28 components, and (d) 3D spectral matrix, 21 components. Nominally the spectral matrix mode (b) is used and samples a 3-channel (U, V, W) spectral matrix with 9 components. Before the frequency averaging (all modes), line noise rejection (RFI mitigation) is applied. It is based on the 'RFI frequency mask pattern' uploaded from the ground.

## (2) The 'Radio-burst' mode for Occultations

Radio-burst mode is primarily used during occultations of Jovian radio emission by icy moons and their ionospheres. This mode is activated during the flybys of ice moons and on orbits around Ganymede (twice per orbit), when JUICE can see the Jovian HOM radio source above the northern and southern auroral oval through the icy moons' ionosphere on the limb. Total time of measurement of single run can be 10 min. To observe frequency dependent cut-off of the radio emission by the radio occultation, spectral matrix of Jovian radio emissions below ~2 MHz is measured. The mode is focused on fine time and frequency resolutions to trace the cut-off frequency changes associated with the spacecraft-limb relative motion.

The current plan is to sample down-converted waveform with 37 kHz bandwidth by the HF receiver. Its central frequency is swept with 72 steps, 28 kHz interval from 80 kHz to 2096 kHz. To track the variation of spectral features the data is taken with fine time and spectral resolutions (dt = 0.2, 0.5, 1, or 2 seconds and df = ~30 kHz) respectively. In the DPU, these waveforms are converted from raw I/Q waveforms to complex spectrum. The waveforms from three channels (U, V and W) are processed for each sweep step. The spectral matrix with 9 independent components (three auto correlations and six cross correlation components) are created. The 3D spectral matrix with 21 independent components can also be as an option. RFI mitigation is not applied in this mode, because it consumes the processing time and has an impact to the time resolution. The rich data transfer to the Earth is after the selection based on the survey data. The survey data product contains one-tenth samples of the rich data. All of them will be transferred to the Earth as a quick-look data sets of the rich data product.

## (3) The passive sub-surface radar (PSSR) modes

PSSR has three modes to measure the electric characteristics of the surfaces and subsurfaces of Europa, Ganymede, and Calisto by reflections of Jovian radio emissions. PSSR1 and PSSR2 is based on the frequency domain characteristics, and it requires the DPU onboard processes. PSSR3 sends the raw down-converted waveforms for further analyses on the ground.

### A. PSSR1 mode

PSSR1 mode is used to detect interferometry pattern appearing in a frequency-time spectrogram of Jovian radio emission. If the Jovian radio emission is seen as a coherent and continuous radio source, an interferometry pattern can arise from a mixture of Jovian radio waves (directly from source regions near Jupiter) and those reflected from the icy moon surface and subsurface structures. PSSR1 tries to resolve this fine interferometry patterns in the spectral matrix with 2.3 kHz spectral resolution.

The current plan is to produce a single data set by down-converted waveforms scanned by the HF receiver with 296 kHz bandwidth (2048 data points for each waveform, selectable) at 45 frequency steps for 10 MHz span with 222 kHz interval. It consists of short waveforms with the duration of 6.92-msecond at each frequency, and full duration is < 1 sec per sequence. In the DPU, these waveforms are converted from I/Q waveforms to complex spectrum as Radio-Full mode. The waveforms from two channels among U, V and W are processed for each sweep step. After RFI mitigation an averaged spectral matrix is produced.
The rich data product contains 4 spectral matrix components for 4320 frequency channels. The survey data product contains power spectrum of 540 frequency channels. The data transfer to Earth occurs after a selection based on the survey data.

## B. PSSR2 mode

PSSR2 mode is like PSSR1, but for non-continuous Jovian short radio burst, S-burst, a part of the Io decametric radiation (Io-DAM). S-burst has dispersive fine spectral structures so its short duration of several milliseconds can be potentially used like Chirp radar signals. If the S-burst signals reflected from surface and subsurface structures are included in the received signals, the arrival time of the reflected waves will be delayed compared to the direct wave from Jupiter. PSSR2 will operate as a “Doppler-radar” through onboard auto-correlation analysis of the S-burst signals and their reflection shorter than the transmission time (>$500 \text{ km}^2\text{/c} \approx 1.6 \text{ ms}$).

In the current plan a single data set is produced by down-converted waveforms scanned by HF receiver with 296 kHz bandwidth (2048 data points for each waveform) at 45 frequency steps (+3 dummies for EMC checks). It consists of short waveforms with the duration of 6.92 ms at each frequency. In the DPU, these waveforms are converted to complex spectrum with FFT, their power spectrum, and finally the auto-correlation functions with inverse FFT. The rich data product contains 16 auto-correlation functions from the U, V, or W-channel (one channel among three) with fine lag-time resolution (2048 steps). Those are selected from measured 45+3 frequency channels, based on the greater auto-correlation values at the zero lag-time (i.e., total signal power). The data transfer to the Earth is after the selection based on the survey data.

## C. PSSR3 mode

PSSR3 mode obtains raw down-converted waveforms, which are the mixture of direct waves coming from Jupiter and reflected waves from icy moon surface and subsurface structures. The plan is to sample a single data set for about 10 seconds/sequence cycle, with a set of 128 waveforms during 11.2 ms each in intervals of 77.8 ms. The data samples a single centre frequency at several 100 kHz to a few MHz, for the correlation analyses on the ground.

The rich data product is the down-converted I/Q waveforms in U, V, and W with 296 kHz bandwidth (2048 data points for each waveform). This data is transferred to the Earth without any further processing in DPU. The single data is large, 54 Mbit per sequence cycle. Therefore, the data transfer occurs to Earth after a selection based on the survey data.

The survey data product is the auto-correlation function in U, V, and W, with 128 lag-time steps for short waveforms in the rich data. For this product, the DPU converts raw I/Q waveforms to complex spectrum with FFT, makes their power spectrum, and produces the final auto-correlation functions with inverse FFT. The single data is not large, 61 kbit (with 10-sec duration). This data will be fully transferred to the Earth as a quick-look data sets of the rich data product.

# 6 RPWI Operations

## 6.1 Concept of RPWI Operations

The RPWI operations are designed to meet the overall science objectives of the JUICE mission (see JUICE Science Working Team 2014). This means a continuous sampling of the near DC electric field is required, so is the monitoring of all electromagnetic and plasma
<table><caption>**Table 16** Current solid state mass memory allocation to RPWI</caption><thead><tr><th>RPWI SSMM allocation</th><th>Gbit</th></tr></thead><tbody><tr><td>Selector 1 (In-Situ)</td><td>10</td></tr><tr><td>Bulk 1 (In-Situ)</td><td>170</td></tr><tr><td>Selector 2 (Radio)</td><td>5</td></tr><tr><td>Bulk 2 (Radio)</td><td>15</td></tr><tr><td>Selected (S/C control)</td><td>2</td></tr></tbody></table>

wave modes and the dynamics of the thermal plasma. Below we describe briefly the common RPWI operation modes, while a more detailed description would be found in the continuously maintained operation mode documents of RPWI. It is therefore recommended that a contact is made with the PI institute when analysing the data to understand possible features of how the instrument is operated at a given time.

## 6.2 SSMM Partition and Selective Downlink

The science operations at Jupiter are based on the selective downlink method to gain high quality data. The Solid-State Mass Memory (SSMM) onboard JUICE and its partition for RPWI is given in Table 16 (can be changed in-flight).

The allocation is based on calculated RPWI TM rates at Jupiter and expected operation sequences, where a couple of examples are presented in Sect. 6.3 below. The selector (or survey) data is always downlinked. The table numbers assume a 4-week (28 days) turnaround period for selecting high resolution (Bulk or rich) data time periods for downlink. The time-periods of bulk data selection to be downlinked are made by an RPWI scientist on duty continuously analysing the selector data. The selector data consist of the continuous electric field (24 sps), the Langmuir probe sweeps from 2 probes, basic wave spectral parameters, dust signals, and radio spectral matrix components. During early cruise operations close to Earth, all RPWI data (selector + bulk) will be downloaded by ESA MOC (i.e., no selective downlink active).

## 6.3 RPWI Science Modes

The RPWI can be run in many operation mode configurations. Some of the more common currently implemented are listed in Table 17. All are run in operation cycles with a common length of 30 seconds, but can be longer, e.g., 600 seconds to reduce TM needs (e.g., in the Jovian magnetosphere).

### 6.3.1 Sequence Cycle Examples

Nominally a set of RPWI measurements will be run in a specific sequence cycle scheme. An example is illustrated below (Table 18). The duration of a sequence cycle can be varied but is here set to default 30 seconds (to fit at least 16,384 samples at 763 samples/s). It can be set to be longer to save TM (e.g., 600 s). Most often the Langmuir probes (LP) will measure the waveform electric field in lowpass and various bandpass bands. The exception is the voltage sweeps once per sequence cycle. The electric field measurements are differential between probe-pairs, while the single ended probe measurements monitor the spacecraft potential. The 24 samples-per-second (sps) signal is a down-sampling of the 763 sps data.
<table><caption>**Table 17** Some common operation modes by receiver/active mode</caption><thead><tr><th>Data product</th><th>Samples</th><th>Duration</th><th>Data type</th><th>Res.</th><th>Output TM<sup>1</sup></th></tr></thead><tbody><tr><td colspan="6"><strong>HF receiver</strong></td></tr><tr><td>Radio Full</td><td>3 ant.<br>256 freq.</td><td>1 sweep/cycle</td><td>Spectrum matrix<br>9 components</td><td>12bit</td><td>27.6 kb</td></tr><tr><td>Radio Burst (for<br>limb radio<br>occultation)</td><td>3 ant.<br>72 freq.</td><td>Continuous<br>1 sweep/0.2 s</td><td>Spectrum matrix<br>9 components</td><td>12bit</td><td>7.8 kb/0.2 s</td></tr><tr><td>PSSR-1</td><td>2 ant.</td><td>1 sweep/cycle</td><td>Spectrum matrix<br>12 components<br>4320 freq</td><td>12bit</td><td>6.22 Mb</td></tr><tr><td>PSSR-2</td><td>1 ant.</td><td>Once/cycle</td><td>Auto corr.<br>16 freq<br>2048 samples</td><td>16bit</td><td>5.3 Mb</td></tr><tr><td>PSSR 3</td><td>3 ant.<br>waveform</td><td>Continuous during<br>10 s/cycle</td><td>Waveform 11 ms<br>3328 samples<br>×128</td><td>128bit</td><td>54.5 Mb</td></tr><tr><td colspan="6"><strong>MIME Sweep</strong></td></tr><tr><td>Nominal sweep</td><td>LP-LP or<br>LP-RWI</td><td>2 s/cycle</td><td>1 passive &amp; 1–4 active<br>sweeps dep. on sub-mode</td><td></td><td>13.3 kb</td></tr><tr><td>Slow<br>sub-mode</td><td>LP-LP or<br>LP-RWI</td><td>2 s/cycle</td><td>1 passive sweep<br>1 active sweep</td><td></td><td>3.9 kb</td></tr><tr><td>Relaxation<br>sub-mode</td><td>LP-LP</td><td>2 s/cycle</td><td>1 passive sweep<br>1 active sweep</td><td></td><td>13.3 kb</td></tr><tr><td>Wide Sweep</td><td>1 LP-LP<br>1 LP-RWI</td><td>2 s/cycle</td><td>2 passive sweeps<br>2 active sweeps</td><td></td><td>13.3 kb</td></tr><tr><td>Tracking</td><td>LP-LP or<br>LP-RWI</td><td>2 s/cycle</td><td>1 passive sweep<br>1 active sweep<br>6 active sweeps around<br>freq. of max amplitude</td><td></td><td>13.3 kb</td></tr><tr><td>Track B-field</td><td>LP-LP</td><td>2 s/cycle</td><td>1 passive sweep<br>1 active sweep<br>3 wide noise measurements<br>around f<sub>gyro</sub> harmonics</td><td></td><td>11.8 kb</td></tr><tr><td colspan="6"><strong>LP Sweep</strong></td></tr><tr><td>Nominal sweep</td><td>2 probes<br>±80 V</td><td>2 seconds<br>256 samples</td><td>LP sweep</td><td>21bit</td><td>21.5 kb</td></tr><tr><td>Dense sweep</td><td>2 probes<br>±10 V</td><td>2 seconds<br>512 samples<br>up-down sweep</td><td>Double sweep</td><td>21bit</td><td>43 kb</td></tr><tr><td>Complete sweep<br>(cal)</td><td>4 probes<br>±80 V</td><td>2 seconds<br>20*512 samples</td><td>LP sweep</td><td>21bit</td><td>860 kb</td></tr></tbody></table>
<table><caption>**Table 17** (Continued)</caption><thead><tr><th>Data product</th><th>Samples</th><th>Duration</th><th>Data type</th><th>Res.</th><th>Output TM<sup>1</sup></th></tr></thead><tbody><tr><td>E-field (LP)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>DC E</td><td>4 probes<br>3diff+1<br>single-end</td><td>Continuous<br>763 sps (or 24 sps)</td><td>Waveform</td><td>21bit</td><td>64 kbps<br>(1.9 Mb/30 s)</td></tr><tr><td>Medium δE</td><td>4 probes<br>3diff+1<br>single-end</td><td>16 ksamples<br>49 ksps<br>High pass 50 Hz</td><td>Waveform</td><td>16bit</td><td>1 Mb</td></tr><tr><td>High δE</td><td>4 probes<br>3diff+1<br>single-end</td><td>16 ksamples<br>694 ksps</td><td>Waveform</td><td>14bit</td><td>896 kb</td></tr><tr><td>δE power sweep</td><td>4 probes<br>2 diff</td><td>Freq. sweep<br>40 kHz window<br>128 freq.<br>&lt; 1.5 MHz</td><td>Power spectrum</td><td>21bit</td><td>1.8 Mb</td></tr><tr><td>LF SCM</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>δB</td><td>3 coils</td><td>Continuous 763<br>sps (or 24 sps)</td><td>Waveform</td><td>16bit</td><td>36.6 kbps<br>(1.1 Mb/30 s)</td></tr><tr><td>Medium δB</td><td>3 coils</td><td>16 ksamples<br>49 ksps</td><td>Waveform</td><td>16bit</td><td>768 kb</td></tr><tr><td colspan="6">LF (Parameters with use of LP E-field probes and SCM data)</td></tr><tr><td>Dust param:s</td><td>4 probes</td><td>Continuous trigger<br>49 ksps</td><td>Dust count</td><td></td><td></td></tr><tr><td>Spectral matrix</td><td>4 probes +<br>3 coils</td><td>Continuous 49<br>ksps</td><td>Spectral parameters</td><td></td><td></td></tr></tbody></table>

As can be seen from Table 18 a RPWI measurement cycle gains substantial information about the plasma and electromagnetic environment. The cycles are repeated continuously and at Jupiter the lower TM survey data (always downloaded) will be used to select on ground the full set of measurements cycles to be downlinked. In this way RPWI will be able to select rich data where interesting events for science occur, i.e., higher science quality data will be kept.

A special thermal plasma density mode can be run where the targets are higher density cases (>100 cm⁻³ plasma), like during low altitude <500 km icy moons flybys, or in orbit around Ganymede. The purpose is to gain high time resolution plasma density (and dust population charge state). The 763 sps (and 24 sps) sampling is then run with a voltage bias and the Langmuir probes sample instead the current giving the density. The voltage bias can be either positive (sampling electrons) or negative (sampling ions) to be sensitive to regions with substantial amounts of negative ions/dust (if existing). There is also the possibility of running all four Langmuir probes in a δn/n interferometry mode at 49 ksps. The bias voltage is set to +4 V or −4 V in all these cases sampling electrons and positive ions respectively.

<footnote n="1">1) Before compression & assuming a sequence cycle length (usually 30–600 s) where applicable.</footnote>
<table><caption>**Table 18** Example of a RPWI sequence cycle of 30 seconds (given in top row). JENRAGE (yellow, HF), MIME (grey, LP, Tx/Rx), GANDALF (brown, LP) and SAMWISE (orange, LP and SCM) measure in electric field (e, sand-colour, LP), magnetic field (b, green, SCM) or in current sampling modes (blue, LP) where voltage sweeps (vs) occur. Certain SAMWISE output products use both electric and magnetic field measurements (light green)</caption><thead><tr><th>Receiver</th><th>Product</th><th>+0</th><th>+2</th><th>+4</th><th>+5</th><th>+6</th><th>+7</th><th>+30 s</th></tr></thead><tbody><tr><td>HF</td><td>Radio Full (3 RWI antenna)</td><td></td><td></td><td></td><td colspan="4">e, 1 freq. sweep</td></tr><tr><td>LP</td><td>MIME Nominal sweep</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">LP</td><td>LP Sweep (P1, ±80V)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>LP Sweep (P2, ±80V)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>E-field (diff P3/P4 & P4)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">LF/SCM</td><td>DC E 24sps</td><td></td><td></td><td></td><td></td><td></td><td></td><td>e</td></tr><tr><td>3diff + 1x single ended P4</td><td></td><td></td><td></td><td></td><td></td><td></td><td>e</td></tr><tr><td rowspan="2">LF</td><td>DC E_763sps</td><td></td><td></td><td></td><td></td><td></td><td></td><td>e</td></tr><tr><td>3diff + 1x single ended P4</td><td></td><td></td><td></td><td></td><td></td><td></td><td>e</td></tr><tr><td rowspan="2">LF/SCM</td><td>B_763sps</td><td></td><td></td><td></td><td></td><td></td><td>b</td><td></td></tr><tr><td>B 49ksps snaps, 16k</td><td></td><td></td><td></td><td></td><td></td><td>b</td><td></td></tr><tr><td rowspan="4">LP</td><td>E_49ksps snaps (all probes), 16k</td><td></td><td></td><td></td><td></td><td></td><td>e</td><td></td></tr><tr><td>Dust parameters (all probes)</td><td></td><td></td><td></td><td></td><td></td><td>e</td><td></td></tr><tr><td>Spectral Matrix (all probes)</td><td></td><td></td><td></td><td></td><td></td><td>e+b</td><td></td></tr><tr><td>Survey Wave params (all probes)</td><td></td><td></td><td></td><td></td><td></td><td>e+b</td><td></td></tr><tr><td>LP</td><td>E_694ksps snaps, 16k, 3 diff + 1x single ended P4</td><td></td><td></td><td></td><td></td><td></td><td>e</td><td></td></tr></tbody></table>

## 6.4 RPWI in-Flight Calibration and Activities

This includes routine health checks of the instrument parts, Langmuir probe surface decontamination, cross-sensor/receiver inter-calibrations, routine calibration signals, tests of uploaded new operation modes, and interference runs with all S/C and other instruments.

The cross-comparisons of independently determined data by RPWI is carried out to verify and improve the interpretation of the data in terms of physical quantities such as density, vector electric field, wave intensity, wave direction finding etc. It also aims to compensate for sensitivity drifts during changing temperatures of all sensors/pre-amps + receivers during different mission phases. The Langmuir probe surface decontamination is run intermittently to sputter the LP sensor surfaces with electrons at +80 V for a continuous time duration of a few days.

The RPWI in-flight calibration activities also includes more complex and dedicated S/C manoeuvres and payload operations, often with simultaneous J-MAG and PEP operations. Three specific types of activities will be mentioned here, all carried out before insertion into Jupiter orbit of JUICE in 2031. These are:

* GANDALF in-flight calibration with full 3D S/C rolls in the solar wind.

* JENRAGE in-flight calibration with partial S/C rolls near Earth.

* Calibration in known plasma and electromagnetic environments near Earth.

### 6.4.1 GANDALF In-Flight Calibration with S/C Rolls

The main purpose of these S/C rolls over an extended time is to gain a complete information of the S/C environment electric and plasma response obtained over the full spacecraft pointing range within the reasonably well-known solar wind environment. This allows for
a determination of the photoelectron and plasma ram wake environment response near the spacecraft and makes it possible to do an accurate near DC electric field calibration to be used during the Jovian phases. The calibration therefore needs measurements of the near DC E-field and plasma environment for the full range of S/C attitudes with respect to the Sun. Simultaneous J-MAG and PEP observations will help characterize the space environment. The activity is planned to occur in the solar wind beyond 1.36 AU due to thermal constraints.

### 6.4.2 JENRAGE in-Flight Calibration with Partial S/C Rolls

The JENRAGE experiment needs in-flight calibration versus foremost Earth's Auroral Kilometric Radiation (AKR) together with S/C rolls (around the axis of the HGA). The calibration activity is used to find the effective RWI antenna pattern and polarization capability with use of the known AKR source in the frequency range 100–800 kHz. When JUICE is not too far from the Earth, solar type-III radio burst in >1 MHz will also be used for effective RWI antenna length calibration together with observations from ground-based radio observatory and Earth-orbiting spacecraft like Arase, Wind, etc. The calibration facilitates the sensitivity and direction finding with the JENRAGE experiment. Currently all three JUICE Earth flybys within 300 $R_{Earth}$ are considered for this activity.

### 6.4.3 Calibration in Known Plasma and Electromagnetic Environments Near Earth

The processing chain implemented in the RPWI experiments have so far relied primarily on internal calibration signals. The onboard processing needs to be calibrated, verified, and validated in a known plasma and electromagnetic environment during in-flight during the Earth flybys, and these are therefore a necessary component for a successful science mission. It needs an extended period starting when JUICE is within the solar wind near Earth, before entering the known Earth space environments, and back in the solar wind. Simultaneous J-MAG and PEP observations will help characterize the space environment. The Earth (and lunar) flybys also give us an opportunity to calibrate the on-board dust counting algorithm for spacecraft impact generated electric signals propagating to and detected by the Langmuir probes. These electric pulses of dust hits on the spacecraft are recorded by all probes in their waveforms.

## 7 RPWI Data Products

### 7.1 Ground Segment Data Processing Pipeline & Archiving

#### 7.1.1 Introduction

The JUICE/RPWI ground segment data pipeline software will process raw and opaque TM files, i.e., CCSDS packets which are generated by the RPWI FSW and handled by various spacecraft and ESA ground station systems, and then convert them into user-friendly datasets in the form of CDF files. This processing covers (1a) RPWI HK and (1b) event data (packets), both for which the format is described wholly by the RPWI MIB, and (2) RPWI science data, which is partly described by the RPWI MIB and partly by the RPWI FSW.

Every science dataset will be generated on one of a set of standardized and ordered processing levels (or “archiving levels”): L1a, L1b, L2, or L3. In general, science datasets will be derived from one or multiple science datasets on the immediately lower processing
level and possibly also from HK datasets. HK datasets and science datasets on the lowest level, L1a, will be generated from TM files. In this manner, science data will be processed in steps from CCSDS packets into more and more refined data products: first to uncalibrated L1a datasets which use non-dimensional TM/ADC units, then to calibrated L1b datasets which use the physical units of the physical instrument, and then further to L2 and L3 which use various calibrated and “derived” quantities, such as e.g., plasma density and E-field using physical units. Datasets can also potentially be derived from combinations of RPWI datasets and datasets from other JUICE experiments when beneficial.

The full pipeline will be split into separate software components that process data for dif-
ferent steps in this chain, and which can be independently operated, as detailed below. In ad-
dition, the RPWI GS will also supply software for generating quick looks for RPWI datasets.
The “TM2RAW” component will use RPWI TM files as input to produce uncalibrated L1a
datasets, while the “RAW2CAL” component will use uncalibrated L1a datasets as input to
produce L1b science-quality calibrated datasets. Further processing of L1b datasets to pro-
duce L2 and L3 datasets will be performed by a “High-level pipeline”. All datasets will be
compliant with both the PDS4 and ISTP archiving standards. All datasets will be validated
and archived by the ESA PSA. The TM2RAW and RAW2CAL components of the pipeline
will be delivered to SOC either in the form of docker images or git repos (for generating
docker images). SOC will then execute the s/w components inside docker containers in or-
der to process RPWI TM files into L1a and L1b datasets for immediate official archiving.
Official L2 and L3 data generation will be handled by the pipeline at IRF.

The full pipeline, from TM to the highest processing levels, is at the time of writing
not yet complete. The TM2RAW component was successfully used during RPWI commis-
sioning for the purposes of near real time conversion of TM to usable CDFs for all HK
and event data, and for most types of RPWI science data. It has further been successfully
used internally for verifying the functioning of both the physical instrument as well as the
RPWI FSW (including FSW upgrades), as well as for miscellaneous ancillary tasks such
as estimating granular TM volumes. The major remaining features to be implemented for
TM2RAW are: support for time conversion from s/c clock to UTC using SPICE kernels,
RPWI-specific time adjustments of science data, support for remaining science data prod-
ucts, various compliance with archiving standards (ISTP, PDS4 labels), and compliance with
interface specifications for running the software at SOC.

7.1.2 TM2RAW Implementation and Features

The TM2RAW is implemented (see Fig. 63) from scratch in Python 3.8 except for the support for decompression of RPWI science data which is implemented in C though accessed through a Python wrapper. TM2RAW is constituted of six standard Python distribution packages, each one installable using the standard Python tool “pip”. It has been developed using CI/CD in the form of git/GitLab combined with automated tests and style checks.

The main TM2RAW distribution package, developed at IRF, handles all CCSDS packets as far as they are described by CCSDS standard and the RPWI MIB and also writes the output CDF files (datasets). The RPWI-specific compression of science data is handled by a separate Python distribution package. The processing of custom-formatted science data is delegated to four separate “plugins” to the main software, separately referred to as Science Data Unpacking Softwares (SDUS’s) and each one implemented as a separate Python distribution package. There is one SDUS for each of four physical subsystems: LP, LF, HF, and MIME. TM originating from the RPWI SCM subsystem is handled by the LF SDUS.

The main TM2RAW distribution package identifies and parses all CCSDS packets as far
as possible using the CCSDS standard and the RPWI MIB. For science data specifically,
<figure><img src="image_68.png" /><figcaption>**Fig. 63** An overview over the separate conceptual modules that make up the TM2RAW part of the RPWI ground segment pipeline, plus the RPWI quick look software and the SOC-provided PDS packager. All the components in the figure will be run by SOC</figcaption></figure>

it uses the CCSDS packet sequence control to reconstruct and extract “science packets” (longer units of science data constructed by the RPWI FSW) from the TM. These science packets are then used as input to the SDUS’s. The SDUS’s in turn return in-memory data structures that describe the bulk content of the corresponding datasets (CDF files), including explicit CDF variables and custom metadata. This delegation of processing to the SDUS’s makes it possible to outsource the de-commutation of custom-formatted science data, as well as outsource the corresponding dataset design to those consortium partners who are responsible for the corresponding hardware, while simultaneously minimizing the development efforts required by those consortium partners.

Additional TM2RAW features include logging, sophisticated built-in statistics of the TM and processing which is used for debugging and monitoring TM and SDUS’s, support for multiple TM file formats and packet headers, a powerful system for layered incremental configurations of the software, and the capacity to generate additional unofficial datasets for debugging, e.g., global lists of all CCSDS packets and science packets respectively. It also contains special features for mitigating shortcomings and known bugs in the first version of the RPWI FSW.

### 7.1.3 RAW2CAL and High-Level Pipeline

The “RAW2CAL” s/w component (L1a-to-L1b) will use uncalibrated L1a datasets as input to produce L1b science-quality calibrated datasets. This component will be developed and tested during the JUICE cruise phase. The specifics of the calibration, e.g., of LP measurements, will be covered in future papers. Broadly speaking, every L1a data product will be directly calibrated using standard techniques to generate a corresponding L1b data product. Higher-level products, L2 and L3, are more likely to be derived from multiple L1b datasets, e.g., combining electric and magnetic field data to determine Poynting flux, processing of LP current voltage sweeps to determine electron density and temperature, and so forth.
<table><caption>**Table 19** Summarized data products to be generated by RPWI, showing the originating subsystems and sensors, processing levels and other salient information</caption><thead><tr><th>Name</th><th>Subunit</th><th>Sensor</th><th>Measurements</th><th>Processing level</th><th>Comment</th></tr></thead><tbody><tr><td>LP Sweeps</td><td>LP</td><td>LP-PWI</td><td>Current-Voltage sweeps</td><td>L1a, L1b</td><td></td></tr><tr><td>Probe potentials</td><td>LP</td><td>LP-PWI</td><td>Probe voltages (single ended, differential)</td><td>L1a, L1b</td><td>Survey + Snapshot</td></tr><tr><td>E field vectors</td><td>LP</td><td>LP-PWI</td><td>Electric field components</td><td>L1b<br>L2 w. analysis</td><td>Survey + Snapshot</td></tr><tr><td>Frequency sweep products</td><td>LP</td><td>LP-PWI</td><td>Spectral matrix</td><td>L1a, L1b<br>L2 w. analysis</td><td></td></tr><tr><td>LP Sweep products</td><td>LP</td><td>LP-PWI</td><td>Electron & ion density, electron temperature, ion drift speed</td><td>L2</td><td></td></tr><tr><td>Spacecraft potential</td><td>LP</td><td>LP-PWI</td><td>Spacecraft potential</td><td>L2</td><td></td></tr><tr><td>Density fluctuations</td><td>LP</td><td>LP-PWI</td><td>δn/n(t)</td><td>L2</td><td>Survey + Snapshot</td></tr><tr><td>Interferometry</td><td>LP</td><td>LP-PWI</td><td>Group speed from δE or δn/n</td><td>L2<br>L3 w. J-MAG</td><td></td></tr><tr><td>Ocean properties</td><td>LP</td><td>LP-PWI</td><td>Interior conductivity / impedance with depth maps</td><td>L3 w. J-MAG</td><td></td></tr><tr><td>Poynting flux</td><td>LP+LF</td><td>LP-PWI + SCM</td><td>Combined E and B vectors</td><td>L2<br>L3 w. J-MAG</td><td></td></tr><tr><td>Polarization</td><td>LP+LF</td><td>LP-PWI + SCM</td><td>Combined E and B vectors</td><td>L2<br>L3 w. J-MAG</td><td></td></tr><tr><td>Dust counts products</td><td>LF</td><td>LP-PWI</td><td>Amplitude, duration</td><td>L2</td><td></td></tr><tr><td>HF spectral matrix</td><td>HF</td><td>RWI</td><td>Spectral matrix</td><td>L1a, L1b<br>L2</td><td></td></tr><tr><td>HF time series</td><td>HF</td><td>RWI</td><td>Electric field components</td><td>L1a, L1b<br>L2</td><td></td></tr><tr><td>Ice crust properties</td><td>HF</td><td>RWI</td><td>Depth maps</td><td>L3</td><td></td></tr><tr><td>MIME sweep spectra</td><td>MIME</td><td>LP + RWI</td><td>Spectral matrix</td><td>L1a, L1b</td><td></td></tr><tr><td>MIME sweep products</td><td>MIME</td><td>LP + RWI</td><td>Electron density, scalar magnetic field</td><td>L2</td><td></td></tr></tbody></table>

## 7.2 RPWI Data Products

A summary of the intended data products to be produced is given in Table 19. Each row in the table corresponds to a dataset to be generated and archived as part of the relevant PDS4 archive “bundle”. Full descriptions of the final datasets will be contained alongside the datasets themselves within the archive bundles, an RPWI data user’s handbook, and in the metadata contained within the CDF files and the PDS4 label files.
## 8 Conclusions

The Radio & Plasma Wave Investigation (RPWI) onboard the ESA JUicer ICy moons Explorer (JUICE) is described here. The information presented herein can be used as a library look-up source for the future when using the RPWI science data. More than 10,000 pages of further technical information of the RPWI instrument will be stored at ESA and the Swedish Institute of Space Physics (IRF) in Uppsala, and so will the in-flight development of the operations and related modes as they become available. It is therefore wise to keep a contact with the PI institute when analysing the RPWI data. All RPWI data will be available as CDF and PDS data after some proprietary period. The RPWI provides a complete set of highly sensitive plasma and fields instrumentation, and related science investigations, for all JUICE project phases until completion. Together, the integrated RPWI system can carry out an ambitious planetary science investigation in and around the Galilean icy moons and the Jovian space environment. RPWI focuses, apart from cold plasma studies, on the understanding of how, through electrodynamic and electromagnetic coupling, the momentum and energy transfer occur with the icy Galilean moons, their surfaces and salty conductive sub-surface oceans. The RPWI instrument is planned to be operational during most of the JUICE mission, during the cruise phase, in the Jovian magnetosphere, during the icy moon flybys, and in particular Ganymede orbit, and will hopefully deliver data from the near surface during the final crash orbit.

**Acknowledgements** The extensive implementation work of the RPWI system on board JUICE have been supported by the following national and international space agencies, which we are thoroughly thankful for: The Swedish National Space Agency (SNSA, lead agency for RPWI), Swedish Institute of Space Physics (IRF), Japan Aerospace Exploration Agency (JAXA), Centre National d'Etudes Spatiales (CNES) and Centre National de la Recherche Scientifique (CNRS), PRODEX Committees for Poland and Czech Republic and ESA PRODEX Office, Austrian National Agency (FFG), and ESA JUICE project has supported the JUICE/RPWI implementation. We give special recognition to the engineering support from Airbus Defence and Space (ADS) in Toulouse and Friedrichshafen as well as the ESA JUICE project. MH's, LC's, and CMJ's work at DIAS is supported by Science Foundation Ireland Grant 18/FRL/6199. MH is also supported by an ESA OSIP fellowship. Work performed at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility, was supported by the U.S. DOE, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357.

The following companies have contributed to the RPWI implementation: RUAG Space (now Beyond Gravity), ESSDE Teknik, AAC Clyde Space, Matra Électronique, Creotech Instruments S.A., Microtec High-Rel Electronics, G. L. Electronics, Alter Technology TÜV Nord, TESAT-Spacecom, Habia Cable AB, Söderfors, Sweden, Invent GmbH, Braunschweig, Germany, Johann Maier GmbH, Stuttgart, Germany, Swedish Space Corporation (SSC), Your Special Delivery Service (YSDS), and Airbus Poland (PZL). Finally, we thank wholeheartedly the reviewers of this manuscript.

**Funding** Open access funding provided by Uppsala University.

## Declarations

**Competing Interests** The authors declare no competing interests.

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## References

Achilleos N, André N, Blanco-Cano X, et al (2015) Transport of mass, momentum and energy in planetary magnetodisc regions. Space Sci Rev 187:229-299. https://doi.org/10.1007/s11214-014-0086-y

Addison P, Liuzzo L, Arnold H, Simon S (2021) Influence of Europa's time-varying electromagnetic environment on magnetospheric ion precipitation and surface weathering. J Geophys Res Space Phys 126:e2020JA029087. https://doi.org/10.1029/2020JA029087

Alfvén H (1942) Existence of electromagnetic-hydrodynamic waves. Nature 150:405–406. https://doi.org/10.1038/150405d0

Alfvén H (1958) On the theory of magnetic storms and Aurorae. Tellus 10:104–116. https://doi.org/10.1111/j.2153-3490.1958.tb01991.x

Allegrini F, Gladstone GR, Hue V, Clark G, Szalay JR, Kurth WS, et al (2020b) First report of electron measurements during a Europa footprint tail crossing by Juno. Geophys Res Lett 47(18):e2020GL089732. https://doi.org/10.1029/2020GL089732

Allegrini F, Mauk B, Clark G, Gladstone GR, Hue V, Kurth WS, et al (2020a) Energy flux and characteristic energy of electrons over Jupiter's main auroral emission. J Geophys Res Space Phys 125:e2019JA027693. https://doi.org/10.1029/2019JA027693

Allegrini F, Bagenal F, Ebert RW, Louarn P, McComas DJ, Szalay JR, et al (2022) Plasma observations during the 7 June 2021 Ganymede flyby from the Jovian Auroral Distributions Experiment (JADE) on Juno. Geophys Res Lett 49:e2022GL098682. https://doi.org/10.1029/2022GL098682

Alm L, Marklund GT, Karlsson T (2014) In situ observations of density cavities extending above the auroral acceleration region. J Geophys Res Space Phys 119:5286–5294. https://doi.org/10.1002/2014JA019799

Alm L, Li B, Marklund GT, Karlsson T (2015) Statistical altitude distribution of the auroral density cavity. J Geophys Res Space Phys 120:996–1006. https://doi.org/10.1002/2014JA020691

André M, Koskinen H, Matson L, Erlandson R (1988) Local transverse ion energization in and near the polar cusp. Geophys Res Lett 15(1):107–110. https://doi.org/10.1029/GL015i001p00107

André M, Odelstad E, Graham DB, Eriksson AI, Karlsson T, Stenberg Wieser G, Vigren E, Norgren C, Johansson FL, Henri P, Rubin M, Richter I (2017) Lower hybrid waves at comet 67P/Churyumov-Gerasimenko. Mon Not R Astron Soc 469(Suppl_2):S29–S38. https://doi.org/10.1093/mnras/stx868

Arce A, Rodriguez D (2019) JUICE magnetometer boom subsystem. In: Proc. 18. European space mechanisms and tribology symposium 2019. Munich, Germany. https://esmats.eu/esmatspapers/pastpapers/pdfs/2019/arce.pdf

Arnold H, Liuzzo L, Simon S (2019) Magnetic signatures of a plume at Europa during the Galileo E26 flyby. Geophys Res Lett 46:1149–1157. https://doi.org/10.1029/2018GL081544

Asamura K, Shoji M, Miyoshi Y, Kasahara Y, Kasaba Y, Kumamoto A, Tsuchiya F, Matsuda S, Matsuoka A, Teramoto M, Kazama Y, Shinohara I (2021) Cross-energy couplings from magnetosonic waves to electromagnetic ion cyclotron waves through cold ion heating inside the plasmasphere. Phys Rev Lett 127:245101. https://doi.org/10.1103/PhysRevLett.127.245101

Aubier MG, Meyer-Vernet N, Pedersen BM (1983) Shot noise from grain and particle impacts in Saturn's ring plane. Geophys Res Lett 10:5–8. https://doi.org/10.1029/GL010i001p00005

Bagenal F, Dols V (2020) The space environment of Io and Europa. J Geophys Res Space Phys 125:e2019JA027485. https://doi.org/10.1029/2019JA027485

Bagenal F, Sullivan JD (1981) Direct plasma measurements in the Io torus and inner magnetosphere of Jupiter. J Geophys Res 86(A10):8447–8466. https://doi.org/10.1029/JA086iA10p08447

Bagenal F, Sidrow E, Wilson RJ, Cassidy TA, Dols V, Crary FJ, Steffl AJ, Delamere PA, Kurth WS, Paterson WR (2015) Plasma conditions at Europa's orbit. Icarus 261:1–13. https://doi.org/10.1016/j.icarus.2015.07.036

Bagenal F, Wilson RJ, Siler S, Paterson WR, Kurth WS (2016) Survey of Galileo plasma observations in Jupiter's plasma sheet. J Geophys Res, Planets 121:871–894. https://doi.org/10.1002/2016JE005009

Bagenal F, Adriani A, Allegrini F, Bolton SJ, Bonfond B, Bunce EJ, et al (2017b) Magnetospheric science objectives of the Juno mission. Space Sci Rev 213:219–287. https://doi.org/10.1007/s11214-014-0036-8

Bagenal F, Dougherty LP, Bodisch KM, Richardson JD, Belcher JM (2017a) Survey of Voyager plasma science ions I: Analysis method. J Geophys Res, Planets 122. https://doi.org/10.1002/2016JA023797

Barabash et al (2025) Space Sci Rev. in preparation

Béghin C, Kolesnikova E (1998) Surface-charge distribution approach for modeling of quasi-static electric antennas in isotropic thermal plasma. Radio Sci 33(3):503–516. https://doi.org/10.1029/97RS03588

Belyaev PP, Polyakov SV, Rapoport VO, Trakhtengerts VY (1990) The ionospheric Alfvén resonator. J Atmos Terr Phys 52(9):781–788. https://doi.org/10.1016/0021-9169(90)90010-K

Bergman JES, Carozzi TD (2007) Systematic characterization of low frequency electric and magnetic field data applicable to Solar Orbiter, proceedings of the 'The second Solar Orbiter workshop' in Athens, Greece (ESA SP-641). ESA Publications Division ESTEC, Noordwijk. ISBN 92-9291-205-2. Preprint. https://arxiv.org/abs/physics/0611073
Bergman S, Stenberg Wieser G, Wieser M, Johansson FL, Eriksson A (2020) The influence of spacecraft charging on low-energy ion measurements made by RPC-ICA on Rosetta. J Geophys Res Space Phys 125(1):e27478. https://doi.org/10.1029/2019JA024748

Bhattacharyya D, Clarke JT, Montgomery J, Bonfond B, Gérard J-C, Grodent D (2018) Evidence for auroral emissions from Callisto's footprint in HST UV images. J Geophys Res Space Phys 123:364–373. https://doi.org/10.1002/2017JA024791

Block LP (1972) Potential double layers in the ionosphere. Cosm Electrodyn 3:349

Block LP, Fälthammar C-G (1968) Effects of field-aligned currents on the structure of the ionosphere. J Geophys Res 73(15):4807–4812. https://doi.org/10.1029/JA073i015p04807

Blöcker A, Saur J, Roth L (2016) Europa's plasma interaction with an inhomogeneous atmosphere: development of Alfvén wingslet within the Alfvén wings. J Geophys Res Space Phys 121(10):9794–9828. https://doi.org/10.1002/2016JA022479

Blomberg LG, Wahlund J-E, Cumnock JA, Marklund GT, Lindqvist P-A, Morooka M, André M, Eriksson AI (2005) Electric field diagnostics in the Jovian system: brief scientific case and instrumentation overview. In: Proceedings of the 6th IAA International Conference on Low-Cost Planetary Missions, 11–13 October 2005, Kyoto, pp 335–340

Blomberg LG, Cumnock JA, Kasaba Y, Matsumoto H, Kojima H, Omura Y, Moncuquet M, Wahlund J-E (2006a) Electric fields in the Hermean environment. Adv Space Res 38:627–631. https://doi.org/10.1016/j.asr.2005.02.034

Blomberg LG, Matsumoto H, Bougeret J-L, Kojima H, Yagitani S, Cumnock JA, Eriksson AI, Marklund GT, Wahlund J-E, Bylander L, Åhlén L, Holtet JA, Ishisaka K, Kallio E, Kasaba Y, Matsuoka A, Moncuquet M, Mursula K, Omura Y, Trotignon J-G (2006b) MEFISTO - an electric field instrument for BepiColombo/MMO. Adv Space Res 38:672. https://doi.org/10.1016/j.asr.2005.05.032

Bochet M, Bergman S, Holmberg MKG, Wieser M, Wieser GS, Wittmann P, et al (2023) Perturbations of JUICE/JDC ion measurements caused by spacecraft charging in the Jovian magnetosphere and the ionosphere of Ganymede. J Geophys Res Space Phys 128:e2023JA031377. https://doi.org/10.1029/2023JA031377

Boehm MH, Carlson CW, McFadden JP, Clemmons JH, Mozer FS (1990) High-resolution sounding rocket observations of large-amplitude Alfvén waves. J Geophys Res 95(A8):12157–12171. https://doi.org/10.1029/2009JA095iA08p12157

Bonfond B, et al (2015) The far-ultraviolet main auroral emission at Jupiter - Part 1: Dawn-dusk brightness asymmetries. Ann Geophys 33:1203

Bonfond B, Saur J, Grodent D, Badman SV, Bisikalo D, Shematovich V, Gérard J-C, Radioti A (2017) The tails of the satellite auroral footprints at Jupiter. J Geophys Res Space Phys 122:7985–7996. https://doi.org/10.1002/2017JA024370

Bonfond B, Yao Z, Grodent D (2020) Six pieces of evidence against the corotation enforcement theory to explain the main aurora at Jupiter. J Geophys Res Space Phys 125:e2020JA028152. https://doi.org/10.1029/2020JA028152

Borovsky JE, Delzanno GL, Valdivia JA, Moya PS, Stepanova M, Birn J, Blum LW, Lotko W, Hesse M (2020) Outstanding questions in magnetospheric plasma physics: the Pollenzo view. J Atmos Sol-Terr Phys 208:105377. https://doi.org/10.1016/j.jastp.2020.105377

Boström R (1964) A model of the auroral electrojets. J Geophys Res 69(23):4983–4999. https://doi.org/10.1029/JZ069i023p04983

Boudouma A, Zarka P, Magalhães FP, Marques MS, Louis CK, Echer E, Lamy L, Prangé R (2023) Localisation of the main HOM source in the dusk side of the Jovian magnetosphere. In: Louis CK, Jackman CM, Fischer G, Sulaiman AH, Zucca P (eds) Planetary, solar and heliospheric radio emissions IX. DIAS, TCD. https://doi.org/10.25546/103094.

Bougeret J-L, et al (1995) WAVES: The radio and plasma wave investigation on the WIND spacecraft. Space Sci Rev 71:231–263. https://doi.org/10.1007/BF00751331

Brogren M, Harding GL, Karmhag R, Ribbing CG, Niklasson GA, Stenmark L (2000) Titanium–aluminum–nitride coatings for satellite temperature control. Thin Solid Films 370(1–2):268–277. https://doi.org/10.1016/S0040-6090(00)00914-7

Brown S, Janssen M, Adumitroaie V, Atreya S, Bolton S, Gulkis S, Ingersoll A, Levin S, Li C, Li L, Lunine J, Misra S, Orton G, Steffes P, Tabataba-Vakili F, Kolmasova I, Imai M, Santolik O, Kurth W, Hospodarsky G, Gurnett D, Connerney J (2018) Prevalent lightning sferics at 600 megahertz near Jupiter's poles. Nature 558:87–90. https://doi.org/10.1038/s41586-018-0156-5

Bruzzone L, Alberti G, Catallo C, Ferro A, Kofman W, Orosei R (2011) Subsurface radar sounding of the Jovian moon Ganymede. In: Proceedings of the IEEE, vol 99, pp 837–857. https://doi.org/10.1109/JPROC.2011.2108990

Bruzzone L et al (2025) Space Sci Rev. in preparation
Bucciantini L, Henri P, Wattiaux G, Califano F, Vallières X, Randriamboarison O (2022) In situ space plasma diagnostics with finite amplitude active electric experiments: non-linear plasma effects and instrumental performance of mutual impedance experiments. J Geophys Res Space Phys 127:e2022JA030813. https://doi.org/10.1029/2022JA030813

Bucciantini L, Henri P, Wattiaux G, Lavorenti F, Dazzi P, Vallières X (2023) Space plasma diagnostics and spacecraft charging. The impact of plasma inhomogeneities on mutual impedance experiments. J Geophys Res Space Phys 128:e2023JA031534. https://doi.org/10.1029/2023JA031534

Buccino DR, Parisi M, Gramigna E, Gomez-Casajus L, Tortora P, Zannoni M, Caruso A, Park RS, Withers P, Steffes P, Hodges A, Levin S, Bolton S (2022) Ganymede's ionosphere observed by a dual-frequency radio occultation with Juno. Geophys Res Lett. https://doi.org/10.1029/2022GL098420

Burke BF, Franklin KL (1955) Observations of a variable radio source associated with the planet Jupiter. J Geophys Res 60(2):213–217. https://doi.org/10.1029/JZ060i002p00213

Carberry Mogan SR, Tucker OJ, Johnson RE, Roth L, Alday J, Vorburger A, et al (2022) Callisto's atmosphere: first evidence for H₂ and constraints on H₂O. J Geophys Res, Planets 127:e2022JE007294. https://doi.org/10.1029/2022JE007294

Carnielli G, Galand M, Leblanc F, Leclercq L, Modolo R, Beth A, Huybrighs HLF, Jia X (2019) First 3D test particle model of Ganymede's ionosphere. Icarus 330:42–59. https://doi.org/10.1016/j.icarus.2019.04.016

Carnielli G, Galand M, Leblanc F, Modolo R, Beth A, Jia X (2020a) Constraining Ganymede's neutral and plasma environments through simulations of its ionosphere and Galileo observations. Icarus 343:113691. https://doi.org/10.1016/j.icarus.2020.113691

Carnielli G, Galand M, Leblanc F, Modolo R, Beth A, Jia X (2020b) Simulations of ion sputtering at Ganymede. Icarus 351:113918. https://doi.org/10.1016/j.icarus.2020.113918

Carozzi TD, Karlsson R, Bergman JES (2001) Parameters characterizing electromagnetic wave polarization. Phys Rev E 61(2):2024–2028. https://doi.org/10.1103/PhysRevE.61.2024

Carrer L, Schroeder DM, Romero-Wolf A, Ries PA, Bruzzone L (2020) Analysis of temporal and structural characteristics of Jovian radio emissions for passive radar sounding of Jupiter's Icy Moons. IEEE Trans Geosci Remote Sens 59(5):3857–3874

CCSDS standard 121.0-B-3 - LOSSLESS DATA COMPRESSION, Consultative Committee for Space Data Systems, 2020. https://public.ccSDS.org/Pubs/121x0b3.pdf

Cecconi B (2013) Goniopolarimetric techniques for low-frequency radio astronomy in space. In: Huber MCE, et al (eds) Observing photons in space. Scientific Report Series, vol 9. Springer, New York. https://doi.org/10.1007/978-1-4614-7804-1_15

Cecconi B, Zarka P (2005) Direction finding and antenna calibration through analytical inversion of radio measurements performed using a system of 2 or 3 electric dipole antennas. Radio Sci 40:RS3003. https://doi.org/10.1029/2004rs003070

Cecconi B, Bougeret J-L, Dekkali M, Lamy L, Zarka P, André N (2010). EJSM Electro-Magnetic Sensor Study (1.7). Zenodo. https://doi.org/10.5281/zenodo.2532436

Cecconi B, Hess S, Hérique A, Santovito MR, Santos-Costa D, Zarka P, Alberti G, Blankenship D, Bougeret J-L, Bruzzone L, Kofman W (2012) Natural radio emission of Jupiter as interferences for radar investigations of the icy satellites of Jupiter. Planet Space Sci 61:32–45. https://www.doi.org/10.1016/j.pss.2011.06.012

Cecconi B, Louis CK, Crego CM, Vallat C (2021) Jovian auroral radio source occultation modelling and application to the JUICE science mission planning. Planet Space Sci 209:1–34. https://doi.org/10.1016/j.pss.2021.105344

Chané E, Saur J, Poedts S (2013) Modeling Jupiter's magnetosphere: influence of the internal sources. J Geophys Res Space Phys 118:2157–2172. https://doi.org/10.1002/jgra.50258

Chasseraux JM, Debrie R, Renard C (1972) J Plasma Phys 8:231–253. https://doi.org/10.1017/S0022377800007108

Chaston CC, Peria WJ, Carlson CW, Ergun RE, McFadden JP (2001) FAST observations of inertial Alfvén waves and electron acceleration in the dayside aurora. Phys Chem Earth, Part C, Sol-Terr Planet Sci 26(1–3):201–205. https://doi.org/10.1016/S1464-1917(00)00108-2

Chaston CC, Salem C, Bonnell JW, Carlson CW, Ergun RE, Strangeway RJ, McFadden JP (2008) The turbulent Alfvénic aurora. Phys Rev Lett 100:175003. https://doi.org/10.1103/PhysRevLett.100.175003

Chauhan KV, Rawal SK (2014) A review paper on tribological and mechanical properties of ternary nitride based coatings. Proc Technol 14(supplement c):430–437. https://doi.org/10.1016/j.protcy.2014.08.055

Chave AD, Jones AG (2012) The magnetotelluric method: theory and practice. Cambridge University Press, Cambridge

Chmyrev VM, Berthelier A, Jorjio NV, Berthelier JJ, Bosqued JM, Galperin YuI, Kovrazhkin RA, Beghin C, Mogilevsky MM, Bilichenko SV, Molchanov OA (1989) Non-linear Alfvén wave generator of auroral particles and ELF/VLF waves. Planet Space Sci 37(6):749–759. https://doi.org/10.1016/0032-0633(89)90044-5
Chust T, Louarn P, Volwerk M, de Feraudy H, Roux A, Wahlund J-E, Holback B (1998) Electric fields with a large parallel component observed by the Freja spacecraft: artifacts or real signals? J Geophys Res 103(A1):215-224. https://doi.org/10.1029/97JA02587

Clark G, Tao C, Mauk BH, Nichols J, Saur J, Bunce EJ, et al (2018) Precipitating electron energy flux and characteristic energies in Jupiter's main auroral region as measured by Juno/JEDI. J Geophys Res Space Phys 123:7554-7567. https://doi.org/10.1029/2018JA025639

Clarke JT, et al (2009) Response of Jupiter's and Saturn's auroral activity to the solar wind. J Geophys Res 114:A05210. https://doi.org/10.1029/2008JA013694

Collet B, Lamy L, Louis CK, Zarka P, Prangé P, Louarn P, Sulaiman A, Kurth WSK (2023) Characterization of Jovian hectometric sources with Juno: statistical position and generation by shell-type electrons. In: Louis CK, Jackman CM, Fischer G, Sulaiman AH, Zucca P (eds) Dublin institute for advanced studies, planetary, solar and heliospheric radio emissions IX. https://doi.org/10.25546/103095

Connerney JEP, Timmins S, Oliversen RJ, Espley JR, Joergensen JL, Kotsiaros S, et al (2022) A new model of Jupiter's magnetic field at the completion of Juno's prime mission. J Geophys Res, Planets 127:e2021JE007055. https://doi.org/10.1029/2021JE007055

Constable S, Parker R, Constable C (1987) Occam's inversion: a practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics 52:289-300. https://doi.org/10.1190/1.1442303

Cook AF, Duxbury TC, Hunt GE (1979) First results on Jovian lightning. Nature 280:794. https://doi.org/10.1038/280794a0

Cowley SWH, Bunce EJ (2001) Origin of the main auroral ovel in Jupiter's coupled magnetosphere-ionosphere system. Planet Space Sci 49:1067-1088. https://doi.org/10.1016/S0032-0633(00)00167-7

Cowley SWH, Deason A, Bunce EJ (2008) Auroral current systems in Jupiter's magnetosphere: predictions for the Juno mission. Ann Geophys 26:4051-4074. https://doi.org/10.5194/angeo-26-4051-2008

Cravens TE, McNutt RL, Waite JH, Robertson IP, Luhmann JG, Kasprzak W, Ip W-H (2009) Plume ionosphere of Enceladus as seen by the Cassini ion and Neutral Mass Spectrometer. Geophys Res Lett 36:L08106. https://doi.org/10.1029/2009GL037811

Cully CM, Angelopoulos V, Auster U, Bonnell J, Le Contel O (2011) Observational evidence of the generation mechanism for rising-tone chorus. Geophys Res Lett 38:L01106. https://doi.org/10.1029/2010GL045793

de Kleer K, Milby Z, Schmidt C, Camarca M, Brown ME (2023) The optical aurorae of Europa, Ganymede, and Callisto. Planet Sci J 4:37. https://doi.org/10.3847/PSJ/acb53c

DeForest SE (1972) Spacecraft charging at synchronous orbit. J Geophys Res 77(4):651-659. https://doi.org/10.1029/JA077i004p00651

Di Paolo F, Lauro SE, Cosciotti B, Mattei E, Pettinelli E (2020) Radar sounding of Ganymede: attenuation and volume scattering losses estimation. EPSC Abstracts 14:EPSC2020-EPSC291. https://doi.org/10.5194/epsc2020-291

Dols VJ, Bagenal F, Cassidy TA, Crary FJ, Delamere PA (2016) Europa's atmospheric neutral escape: importance of symmetrical O2 charge exchange. Icarus 264:387-397. https://doi.org/10.1016/j.icarus.2015.09.026

Dong Y, Hill TW, Ye S-Y (2015) Characteristics of ice grains in the Enceladus plume from Cassini observations. J Geophys Res Space Phys 120:915-937. https://doi.org/10.1002/2014JA020288

Dougherty MK, Khurana KK, Neubauer FM, Russell CT, Saur J, Leisner JS, Burton ME (2006) Identification of a dynamic atmosphere at Enceladus with the Cassini magnetometer. Science 311(5766):1406-1409. https://doi.org/10.1126/science.1120985

Dougherty et al (2025) Space Sci Rev. in preparation

Drell SD, Foley HM, Ruderman MA (1965) Drag and propulsion of large satellites in the ionosphere: an Alfvén propulsion engine in space. J Geophys Res 70:13. https://doi.org/10.1103/PhysRevLett.14.171

Duling S, Saur J, Wicht J (2014) Consistent boundary conditions at nonconducting surfaces of plane-tary bodies: applications in a new Ganymede MHD model. J Geophys Res Space Phys 119:4412-4440. https://doi.org/10.1002/2013JA019554

Edberg NJT, Wahlund J-E, Ågren K, Morooka MW, Modolo R, Bertucci C, Dougherty MK (2010) Electron density and temperature measurements in the cold plasma environment of Titan – implications for atmospheric escape. Geophys Res Lett 37:L20105. https://doi.org/10.1029/2010GL044544

Edberg NJT, Ågren K, Wahlund J-E, Morooka MW, Andrews DJ, Cowley SWH, Wellbrock A, Coates AJ, Bertucci C, Dougherty MK (2011) Structured ionospheric outflow during the Cassini T55-T59 Titan flybys. Planet Space Sci 59(8):788-797. https://doi.org/10.1016/j.pss.2011.03.007

Edberg NJT, Andrews DJ, Shebanits O, Ågren K, Wahlund J-E, Opgenoorth HJ, Cravens TE, Girazian Z (2013) Solar cycle modulation of Titan's ionosphere. J Geophys Res Space Phys 118:5255-5264. https://doi.org/10.1002/jgra.50463
Egbert GD, Erofeeva SY (2002) Efficient inverse modelling of barotropic ocean tides. J Atmos Ocean Technol 19:183-204. https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2

Engelhardt IAD, Wahlund J-E, Andrews DJ, Eriksson AI, Ye S, Kurth WS, Gurnett DA, Morooka MW, Farrell WM, Dougherty MK (2015) Plasma regions, charged dust and field-aligned currents near Enceladus. Planet Space Sci 117:453-469. https://doi.org/10.1016/j.pss.2015.09.010

Ergun RE, Carlson CW, McFadden JP, Mozer FS, Delory GT, Peria W, Chaston CC, Temerin M, Roth I, Muschietti L, Elphic R, Strangeway R, Pfaff R, Cattell CA, Klumpar D, Shelley E, Peterson W, Moebius E, Kistler L (1998) FAST satellite observations of large-amplitude solitary structures. Geophys Res Lett 25(12):2041-2044. https://doi.org/10.1029/98GL00636

Ergun RE, Andersson L, Main D, Su Y-J, Newman DL, Goldman MV, Carlson CW, McFadden JP, Mozer FS (2002) Parallel electric fields in the upward current region of the aurora: numerical solutions. Phys Plasmas 9:3695-3704. https://doi.org/10.1063/1.1499121

Ergun RE, Andersson L, Main D, Su Y-J, Newman DL, Goldman MV, Carlson CW, Hull AJ, McFadden JP, Mozer FS (2004) Auroral particle acceleration by strong double layers: the upward current region. J Geophys Res 109:A12220. https://doi.org/10.1029/2004JA010545

Eriksson AI, Wahlund J-E (2006) Charging of the Freja satellite in the auroral zone. IEEE Trans Plasma Sci 34:2038-2045. https://doi.org/10.1109/TPS.2006.883373

Eriksson AI, Boström R, Gill R, et al (2007) RPC-LAP: the Rosetta Langmuir probe instrument. Space Sci Rev 128:729-744. https://doi.org/10.1007/s11214-006-9003-3

Eriksson I, Engelhardt IAD, André M, Boström R, Edberg NJT, Johansson FL, Odelstad E, Vigren E, Wahlund J-E, Henri P, Lebreton J-P, Miloch WJ, Paulsson JJP, Simon Wedlund C, Yang L, Karlsson T, Jarvinen R, Broiles T, Mandt K, Carr CM, Galand M, Nilsson H, Norberg C (2017) Cold and warm electrons at comet 67P/Churyumov-Gerasimenko. Astron Astrophys 605:A15. https://doi.org/10.1051/0004-6361/201630159

Eriksson AI, Wedin LJ, Wahlund J-E, Holback B Analysis of Freja Charging Events: Modelling of Freja observations by spacecraft charging codes, SPEE-WP 120-TN, under ESA contract 11974/96/NL/JG(SC), IRF Sci. Report 252, 1999, ISSN 0284-1703

Evans S (1965) Dielectric properties of ice and snow - a review. J Glaciol 5:773-792. https://doi.org/10.3189/S0022143000018840

Eviatar A, Vasyliunas VM, Gurnett DA (2001) The ionosphere of Ganymede. Planet Space Sci 49:327-336. https://doi.org/10.1016/S0032-0633(00)00154-9

Fahleson U, Fälthammar C-G, Pedersen A (1974) Ionospheric temperature and density measurements by means of spherical double probes. Planet Space Sci 22:41-66

Farrell WM, Kaiser ML, Desch MD (1999) A model of the lightning discharge at Jupiter. Geophys Res Lett 26:2601-2604. https://doi.org/10.1029/1999GL900527

Farrell WM, Kurth WS, Tokar RL, Wahlund J-E, Gurnett DA, Wang Z, MacDowall RJ, Morooka MW, Johnson RE, Waite JH (2010) Modification of the plasma in the near-vicinity of Enceladus by the enveloping dust. Geophys Res Lett 37:20202. https://doi.org/10.1029/2010GL044768

Farrell WM, Wahlund J-E, Morooka M, Gurnett DA, Kurth WS, MacDowall RJ (2012) The electromagnetic pickup of submicron-sized dust above Enceladus's northern hemisphere. Icarus 219:498-501. https://doi.org/10.1016/j.icarus.2012.02.033

Farrell WM, Wahlund J-E, Morooka M, Gurnett DA, Kurth WS, MacDowall RJ (2014) An estimate of the dust pickup current at Enceladus. Icarus 239:217-221. https://doi.org/10.1016/j.icarus.2014.05.034

Farrell WM, Wahlund J-E, Morooka M, Kurth WS, Gurnett DA, MacDowall RJ (2017) Ion trapping by dust grains: simulation applications to the Enceladus plume. J Geophys Res, Planets 122:729-743. https://doi.org/10.1002/2016JE005235

Fatemi S, Poppe AR, Khurana KK, Holmström M, Delory GT (2016) On the formation of Ganymede's surface brightness asymmetries: kinetic simulations of Ganymede's magnetosphere. Geophys Res Lett 43:4745-4754. https://doi.org/10.1002/2016GL068363

Feldman PD, McGrath MA, Strobel DF, Moos HW, Retherford KD, Wolven BC (2000) HST/STIS ultraviolet imaging of polar aurora on Ganymede. Astrophys J 535:1085. https://doi.org/10.1086/308889

Fischer G, Gurnett DA, Kurth WS, Akalin F, Zarka P, Dyudina UA, Farrell WM, Kaiser ML (2008) Atmospheric electricity at Saturn. Space Sci Rev 137:271-285. https://doi.org/10.1007/s11214-008-9370-z

Fischer G, Panchenko M, Macher W, Kasaba Y, Misawa H, Tokarz M, Wisniewski L, Cecconi B, Bergman J, Wahlund J-E (2021) Calibration of the JUICE RWI antennas by numerical simulation. Radio Sci 56:e2021RS007309. https://doi.org/10.1029/2021RS007309

Fleshman BL, Delamere PA, Bagenal F (2010) Modeling the Enceladus plume-plasma interaction. Geophys Res Lett 37:L03202. https://doi.org/10.1029/2009GL041613

Fletcher LN, Cavalié T, Grassi D, et al (2023) Jupiter science enabled by ESA's JUpiter ICy moons Explorer. Space Sci Rev 219:53. https://doi.org/10.1007/s11214-023-00996-6
Frank LA, Paterson WR, Ackerson KL, Bolton SJ (1997) Outflow of hydrogen ions from Ganymede. *Geo-phys Res Lett* 24:2151. https://doi.org/10.1029/97GL01744

Fujita S, Matsuoka T, Ishida T, Matsuoka K, Mae S (2000) A summary of the complex dielectric permittivity of ice in the megahertz range and its applications for radar sounding of polar ice sheets. *Physics of Ice Core Records*, 185–212. http://hdl.handle.net/2115/32469

Galand M, Carnielli G, Jia X (2025) Ganymede’s ionosphere. In: Volwerk M, McGrath M, Jia X, Spohn T (eds) Ganymede. Cambridge planetary science. Cambridge University Press, Cambridge.

Galli A, Vorburger A, Carberry Mogan SR, Roussos E, Stenberg Wieser G, Wurz P, et al (2022) Callisto’s atmosphere and its space environment: prospects for the particle environment package on board JUICE. *Earth Space Sci* 9:e2021EA002172. https://doi.org/10.1029/2021EA002172

Galopeau PHM, Boudjada MY (2016) An oblate beaming cone for Io-controlled Jovian decameter emission. *J Geophys Res Space Phys* 121:3120–3138. https://doi.org/10.1002/2015JA021038

Gassot O, Herique A, Kofman W, Witasse O (2021) Passive radar probing of the Galilean Moons (No. EPSC2021-521). Copernicus Meetings

Gautier A-L (2013) Étude de la propagation des ondes radio dans les environnements planétaires. (Doctoral dissertation), Observatoire de Paris. https://theses.hal.science/tel-01145651v2

Génot V, et al (2018) Science data visualization in planetary and heliospheric contexts with 3DView. *Planet Space Sci* 150:111–130. https://doi.org/10.1016/j.pss.2017.07.007

Gerekos C, Bruzzone L, Imai M (2019) A coherent method for simulating active and passive radar sounding of the Jovian icy moons. *IEEE Trans Geosci Remote Sens* 58(4):2250–2265

Gershman DJ, Connerney JEP, Kotsiaros S, DiBraccio GA, Martos YM, F.-Viñas A, et al (2019) Alfvénic fluctuations associated with Jupiter’s auroral emissions. *Geophys Res Lett* 46:7157–7165. https://doi.org/10.1029/2019GL082951

Gilet N, Henri P, Wattieaux G Cilibrasi M, Beghin C (2017) Electrostatic potential radiated by a pulsating charge in a two-electron temperature plasma. *Radio Sci* 52:1432

Gilet N, Henri P, Wattieaux G, Myllys M, Randriamboarison O, Béghin C, Rauch J-L (2019) Mutual impedance probe in collisionless unmagnetized plasmas with suprathermal electrons - application to BepiColombo. *Front Astron Space Sci* 6:16. https://doi.org/10.3389/fspas.2019.00016

Gilet N, Henri P, Wattieaux G, Traoré N, Eriksson AI, Vallières X, Moré J, Randriamboarison O, Odelstad E, Johansson FL, Rubin M (2020) Observations of a mix of cold and warm electrons by RPC-MIP at 67P/Churyumov-Gerasimenko. *Astron Astrophys* 640:A110

Giono G, Roth L, Ivchenko N, Saur J, Retherford K, Schlegel S, Ackland M, Strobel D (2020) An analysis of the statistics and systematics of limb anomaly detections in HST/STIS transit images of Europa. *Astrophys J* 159(4):155. https://doi.org/10.3847/1538-3881/ab7454

Gissinger C, Petitdemange L (2019) A magnetically driven equatorial jet in Europa’s ocean. *Nat Astron* 3:401–407. https://doi.org/10.1038/s41550-019-0713-3

Goertz CK (1984) Kinetic Alfvén waves on auroral field lines. *Planet Space Sci* 32(11):1387–1392. https://doi.org/10.1016/0032-0633(84)90081-3

Graham DB, Khyoyaintsev YV, Norgren C, Vaivads A, André M, Drake JF, et al (2019) Universality of lower hybrid waves at Earth’s magnetopause. *J Geophys Res Space Phys* 124. https://doi.org/10.1029/2019JA027155

Grard RJL (1969) Coupling between two electric aerials in a warm plasma. *Alta Freq* 38:97–101

Grayver AV, Olsen N (2019) The magnetic signatures of the *M2*, *N2*, and *O1* Oceanic tides observed in swarm and CHAMP satellite magnetic data. *Geophys Res Lett* 46:4230–4238. https://doi.org/10.1029/2019GL082400

Grayver AV, Schnepf NR, Kuvshinov AV, Sabaka TJ, Manoj C, Olsen N (2016) Satellite tidal magnetic signals constrain Oceanic lithosphere-asthenosphere boundary. *Sci Adv* 2(9):e1600798

Grayver AV, Munch FD, Kuvshinov AV, Khan A, Sabaka TJ, Tøffner-Clausen L (2017) Joint inversion of satellite-detected tidal and magnetospheric signals constrains electrical conductivity and water content of the upper mantle and transition zone. *Geophys Res Lett* 44:6074–6081. https://doi.org/10.1002/2017GL073446

Greathouse TK, Gladstone GR, Molyneux PM, Versteeg MH, Hue V, Kammer JA, et al (2022) UVS observations of Ganymede’s aurora during Juno orbits 34 and 35. *Geophys Res Lett* 49:e2022GL099794. https://doi.org/10.1029/2022GL099794

Grimm RE, et al (2020) A magnetotelluric instrument for probing the interiors of Europa and other worlds. *Adv Space Res*. https://arxiv.org/abs/2101.06730

Grimm R, Castillo-Rogez J, Raymond C, Poppe AR (2021) Feasibility of characterizing subsurface brines on Ceres by electromagnetic sounding. *Icarus* 362:114424. https://doi.org/10.1016/j.icarus.2021.114424

Grygorczuk J, Tokarz M, Wisniewski L, Kucinski T, Ossowski M, Bochra K, Bogonski M, Jarzynka S, Palma P, Ryszawa E, Jarocki K, Wahlund J-E, Bergman J, Kasaba Y, Le Letty R (2023) RWI tubular boom antennas – lessons learned from the development of a flight model for the ESA JUICE Mission, ESMAT
Gunell H, Goetz C, Eriksson A, Nilsson H, Simon Wedlund C, Henri P, Maggiolo R, Hamrin M, De Keyser J, Rubin M, Stenberg Wieser G, Cessateur G, Dhooghe F, Gibbons A (2017a) Plasma waves confined to the diamagnetic cavity of comet 67P/Churyumov-Gerasimenko. Mon Not R Astron Soc 469(Suppl_2):S84-S92. https://doi.org/10.1093/mnras/stx1134

Gunell H, Nilsson H, Hamrin M, Eriksson A, Odelstad E, Maggiolo R, Henri P, Vallieres X, Altwegg K, Tzou C-Y, Rubin M, Glassmeier K-H, Stenberg Wieser G, Simon Wedlund C, De Keyser J, Dhooghe F, Cessateur G, Gibbons A (2017b) Ion acoustic waves at comet 67P/Churyumov-Gerasimenko. Astron Astrophys 600:A3. https://doi.org/10.1051/0004-6361/201629801

Gunell H, Goetz C, Odelstad E, Beth A, Hamrin M, Henri P, Johansson FL, Nilsson H, Stenberg Wieser G (2021) Ion acoustic waves near a comet nucleus: Rosetta observations at comet 67P/Churyumov-Gerasimenko. Ann Geophys 39:53-68. https://doi.org/10.5194/angeo-39-53-2021

Gurnett DA, Frank LA (1977) A region of intense plasma wave turbulence on auroral field lines. J Geophys Res 82(7):1031-1050. https://doi.org/10.1029/JA082i007p01031

Gurnett DA, Show RR, Anderson RR, Kurth WS, Scarf FL (1979) Whistlers observed by Voyager 1: detection of lightning on Jupiter. Geophys Res Lett 6:511-514. https://doi.org/10.1029/GL006i006p00511

Gurnett DA, Grün E, Gallagher D, Kurth WS, Scarf FL (1983b) Micron-sized particles detected near Saturn by the Voyager plasma wave instrument. Icarus 53(2):236-254. https://doi.org/10.1016/0019-1035(83) 90145-8

Gurnett D, Kurth W, Scarf F (1983a) Narrowband electromagnetic emissions from Jupiter's magnetosphere. Nature 302:385-388. https://doi.org/10.1038/302385a0

Gurnett DA, Kurth WS, Scarf FL, Burns JA, Cuzzi JN, Grün E (1987) Micron-sized particle impacts detected near Uranus by the Voyager 2 plasma wave instrument. J Geophys Res 92(A13):14959-14968. https:// doi.org/10.1029/JA092iA13p14959

Gurnett DA, Kurth WS, Granroth LJ, Allendorf SC, Poynter RL (1991) Micron-sized particles detected near Neptune by the Voyager 2 plasma wave instrument. J Geophys Res 96(S01):19177-19186. https://doi. org/10.1029/91JA01270

Gurnett D, Kurth W, Roux A, et al (1996) Evidence for a magnetosphere at Ganymede from plasma-wave observations by the Galileo spacecraft. Nature 384:535-537. https://doi.org/10.1038/384535a0

Gurnett DA, Kurth WS, Roux A, Bolton SJ, Thomsen EA, Groene JB (1998) Galileo plasma wave observations near Europa. Geophys Res Lett 25(3):237-240. https://doi.org/10.1029/97GL03706

Gurnett DA, Persoon AM, Kurth WS, Roux A, Bolton SJ (2000) Plasma densities in the vicinity of Callisto from Galileo plasma wave observations. Geophys Res Lett 27(13):1867-1870. https://doi.org/10.1029/ 2000GL003751

Gurnett DA, Kurth WS, Kirchner DL, Hospodarsky GB, Averkamp TF, Zarka P, Lecacheux A, Manning R, Roux A, Canu P, Cornilleau-Wehrlin N, Galopeau P, Meyer A, Boström R, Gustafsson G, Wahlund J-E, Åhlén L, Rucker HO, Ladreiter HP, Macher W, Woolliscroft LJC, Alleyne H, Kaiser ML, Desch MD, Farrell WM, Harvey CC, Louarn P, Kellogg PJ, Goetz K, Pedersen A (2004) The Cassini Radio and Plasma Wave Investigation. Space Sci Rev 114:395-463. https://doi.org/10.1007/s11214-004-1434-0

Gurnett DA, et al (2011) Auroral hiss, electron beams and standing Alfvén wave currents near Saturn's moon Enceladus. Geophys Res Lett 38:L06102. https://doi.org/10.1029/2011GL046854

Gustafsson G, Wahlund J-E (2010) Electron temperatures in Saturn's plasma disc. Planet Space Sci 58:1018-1025. https://doi.org/10.1016/j.pss.2010.03.007

Haerendel G (2011) Six auroral generators: a review. J Geophys Res 116:A00K05. https://doi.org/10.1029/ 2010JA016425

Hall DT, Strobel DF, Feldman PD, McGrath MA, Weaver HA (1995) Detection of an oxygen atmosphere on Jupiter's moon Europa. Nature 373(6516):677-681. https://doi.org/10.1038/373677a0

Hall DT, Feldman PD, McGrath MA, Strobel DF (1998) The far-ultraviolet oxygen airglow of Europa and Ganymede. Astrophys J 499:475. https://doi.org/10.1086/305604

Harris CDK, Jia X, Slavin JA, Toth G, Huang Z, Rubin M (2021) Multi-fluid MHD simulations of Europa's plasma interaction under different magnetospheric conditions. J Geophys Res Space Phys 126:e2020JA028888. https://doi.org/10.1029/2020JA028888

Harris CDK, Jia X, Slavin JA (2022) Multi-fluid MHD simulations of Europa's plasma interaction: effects of variation in Europa's atmosphere. J Geophys Res Space Phys 127:e2022JA030569. https://doi.org/10. 1029/2022JA030569

Hartkorn O, Saur J (2017) Induction signals from Callisto's ionosphere and their implications on a possible subsurface ocean. J Geophys Res Space Phys 122:11,677-11,697. https://doi.org/10.1002/ 2017JA024269

Hartkorn O, Saur J, Strobel DF (2017) Structure and density of Callisto's atmosphere from a fluid-kinetic model of its ionosphere: comparison with Hubble Space Telescope and Galileo observations. Icarus 282:237-259. https://doi.org/10.1016/j.icarus.2016.09.020
Hartogh P, Ilyushin YA (2016) A passive low frequency instrument for radio wave sounding the subsurface oceans of the Jovian icy moons: an instrument concept. *Planet Space Sci* 130:30–39

Hasegawa A (1976) Particle acceleration by MHD surface wave and formation of aurora. J Geophys Res 81(28):5083–5090. https://doi.org/10.1029/JA081i028p05083

Hess S, Mottez F, Zarka P (2007) Jovian S-bursts generation by Alfvén waves. J Geophys Res 112:A11212

Hess S, Mottez F, Zarka P, Chust T (2008) Generation of the Jovian radio decametric arcs from the Io flux tube. J Geophys Res 113:A03209

Hess SLG, Echer E, Zarka P, Lamy L, Delamere PA (2014) Multi-instrument study of the Jovian radio emissions triggered by solar wind shocks and inferred magnetospheric subcorotation rates. *Planet Space Sci* 99:136–148

Hill TW (1975) Inertial limit on corotation. J Geophys Res 84:6554. https://doi.org/10.1029/JA084iA11p06554

Hill TW (1979) Inertial limit on corotation. J Geophys Res 84(A11):6554–6558. https://doi.org/10.1029/JA084iA11p06554

Hill TW (2001) The Jovian auroral oval. J Geophys Res 106(A5):8101–8810. https://doi.org/10.1029/2000JA000302

Hill TW, et al (2012) Charged nanograins in the Enceladus plume. J Geophys Res 117:A05209. https://doi.org/10.1029/2011JA017218

Hillier JK, Green SF, McBride N, Schwanethal JP, Postberg F, Srama R, Kempf S, Moragas-Klostermeyer G, McDonnell JAM, Grün E (2007) The composition of Saturn's E ring. Mon Not R Astron Soc 377:1588–1596. https://doi.org/10.1111/j.1365-2966.2007.11710.x

Holmberg MKG (2020) JUICE spacecraft charging analysis. ESA Technical note JUI-EST-SYS-TN-026

Holmberg MKG, Wahlund J-E, Morooka MW, Persoon AM (2012) Ion densities and velocities in the inner plasma torus of Saturn. *Planet Space Sci* 73:151–160. https://doi.org/10.1016/j.pss.2012.09.016

Holmberg MKG, Shebanits O, Wahlund J-E, Morooka MW, Vigren E, André N, Garnier P, Persoon AM, Génot V, Gilbert LK (2017) Density structures, dynamics, and seasonal and solar cycle modulations of Saturn's inner plasma disk. J Geophys Res Space Phys 122:12,258–12,273. https://doi.org/10.1002/2017JA024311

Holmberg MKG, Cipriani F, Nilsson T, Hess S, Huybrighs HLF, Hadid LZ, et al (2021) Cassini-plasma interaction simulations revealing the Cassini ion wake characteristics: implications for in-situ data analyses and ion temperature estimates. J Geophys Res Space Phys 126:e2020JA029026. https://doi.org/10.1029/2020JA029026

Holmberg MKG, Jackman CM, Taylor MGGT, Witasse O, Wahlund J-E, Barabash S, et al (2024) Surface charging of the Jupiter Icy Moons Explorer (JUICE) spacecraft in the solar wind at 1 AU. J Geophys Res Space Phys 129:e2023JA032137. https://doi.org/10.1029/2023JA032137

Holmgren G, Kintner PM (1990) Experimental evidence of widespread regions of small-scale plasma irregularities in the magnetosphere. J Geophys Res 95(A5):6015–6023. https://doi.org/10.1029/JA095iA05p06015

Huscher E, Bagenal F, Wilson RJ, Allegrini F, Ebert RW, Valek PW, et al (2021) Survey of Juno observations in Jupiter's plasma disk: density. J Geophys Res Space Phys 126:e2021JA029446. https://doi.org/10.1029/2021JA029446

Imai M, Kolmasova I, Kurth WS, Santolik O, Hospodarsky GB, Gurnett DA, Brown ST, Bolton SJ, Connerney JEP, Levin S (2019) Evidence for low density holes in Jupiter's ionosphere. Nat Commun 10. https://doi.org/10.1038/s41467-019-10708-w

Jacome HRP, Marques MS, Zarka P, Echer E, Lamy L, Louis C (2022) Search for Jovian DAM emissions induced by Europa on the extensive Nançay decameter array's catalog. Astron Astrophys 665:A67. https://doi.org/10.1051/0004-6361/20224426

Janhunen P, Olsson A, Laakso H (2002) Altitude dependence of plasma density in the auroral zone. Ann Geophys 20:1743–1750. https://doi.org/10.5194/angeo-20-1743-2002

Jia X, Walker RJ, Kivelson MG, Khurana KK, Linker JA (2009) Properties of Ganymede's magnetosphere inferred from improved three-dimensional MHD simulations. J Geophys Res 114:A09209. https://doi.org/10.1029/2009JA014375

Jia X, Kivelson MG, Khurana KK, et al (2018) Evidence of a plume on Europa from Galileo magnetic and plasma wave signatures. Nat Astron 2:459–464. https://doi.org/10.1038/s41550-018-0450-z

Johansson FL, et al (2021) Plasma densities, flow, and solar EUV flux at comet 67P a cross-calibration approach. Astron Astrophys 653:A128. https://doi.org/10.1051/0004-6361/202039959

Johnson RE, Burger MH, Cassidy TA, Leblanc F, Marconi M, Smyth WH (2009) Composition and detection of Europa's sputter-induced atmosphere. In: Pappalardo RT, McKinnon WB, Khurana KK (eds) Europa. University of Arizona Press, Tucson, p 507

Jones GH, et al (2009) Fine jet structure of electrically charged grains in Enceladus' plume. Geophys Res Lett 36:L16204. https://doi.org/10.1029/2009GL038284
JUICE Science Working Team (2014) JUICE definition study report (Red Book). ESA/SRE(2014)1. European Space Agency. https://sci.esa.int/web/juice/-/54994-juice-definition-study-report

Karlsson T, Eriksson AI, Odelstad E, André M, Dickeli G, Kullen A, Lindqvist P-A, Nilsson H, Richter I (2017) Rosetta measurements of lower hybrid frequency range electric field oscillations in the plasma environment of comet 67P. Geophys Res Lett 44:1641–1651. https://doi.org/10.1002/2016GL072419

Karlsson T, Andersson L, Gillies DM, et al (2020) Quiet, discrete auroral arcs – observations. Space Sci Rev 216:16. https://doi.org/10.1007/s11214-020-0641-7

Kasahara Y, et al (2018) The plasma wave experiment (PWE) on board the Arase (ERG) satellite. Earth Planets Space 70:86. https://doi.org/10.1186/s40623-018-0842-4

Katoh M, Fujimoto M, Kawaguchi H, Tsuchiya K, Ohmi K, Kaneyasu T, Taira Y, Hosaka M, Mochihashi A, Takashima Y (2017) Angular momentum of twisted radiation from an electron in spiral motion. Phys Rev Lett 118:094801. https://doi.org/10.1103/PhysRevLett.118.094801

Katoh Y, Kojima H, Hikishima M, et al (2018) Software-type wave–particle interaction analyzer on board the arase satellite. Earth Planets Space 70:4. https://doi.org/10.1186/s40623-017-0771-7

Keiling A, Wygant JR, Cattell C, Peria W, Parks G, Temerin M, et al (2002) Correlation of Alfvén wave Poynting flux in the plasma sheet at 4-7 RE with ionospheric electron energy flux. J Geophys Res 107(A7):1132. https://doi.org/10.1029/2001JA900140

Keiling A, Thaller S, Wygant J, Dombeck J (2019a) Assessing the global Alfvén wave power flow into and out of the auroral acceleration region during geomagnetic storms. Sci Adv 5(6):eaav8411. https://doi.org/10.1126/sciadv.aav8411

Keiling A, Thaller S, Wygant J, Dombeck J (2019b) Global Alfvén wave power in the auroral zone in relation to the AE index. J Geophys Res Space Phys 124:8637–8646. https://doi.org/10.1029/2019JA026805

Kempf S, Beckmann U, Srama R, Horanyi M, Auer S, Grün E (2006) The electrostatic potential of E ring particles. Planet Space Sci 54:999–1006. https://doi.org/10.1016/j.pss.2006.05.012

Kempf S, Beckmann U, Moragas-Klostermeyer G, Postberg F, Srama R, Economou T, Schmidt J, Spahn F, Grün E (2008) The E ring in the vicinity of Enceladus. I: Spatial distribution and properties of the ring particles. Icarus 193:420–437. https://doi.org/10.1016/j.icarus.2007.06.027

Kempf S, Beckmann U, Schmidt J (2010) How the Enceladus dust plume feeds Saturn’s E ring. Icarus 206(2):446–457. https://doi.org/10.1016/j.icarus.2009.09.016

Kennel CF, Coroniti FV (1975) Is Jupiter’s magnetosphere like a pulsar’s or Earth’s. Space Sci Rev 17:857–883. https://doi.org/10.1007/BF00777259

Khotyaintsev YY, Cully CM, Vaivads A, André M, Owen CJ (2011) Plasma jet braking: energy dissipation and nonadiabatic electrons. Phys Rev Lett 106:16500. https://doi.org/10.1103/PhysRevLett.106.165001

Khotyaintsev YY, Graham DB, Norgren C, Vaivads A (2019) Collisionless magnetic reconnection and waves: progress review. Front Astron Space Sci 6:70. https://doi.org/10.3389/fspas.2019.00070

Khotyaintsev YuV, et al (2021) Density fluctuations associated with turbulence and waves – first observations by Solar Orbiter. Astron Astrophys 656:A19. https://doi.org/10.1051/0004-6361/202140936

Khorana KK, Kivelson MG (1999) Inner Jovian magnetosphere: mass-loading near Europa. Eos 80:F875

Khorana K, Kivelson M, Stevenson D, et al (1998) Induced magnetic fields as evidence for subsurface oceans in Europa and Callisto. Nature 395:777–780. https://doi.org/10.1038/27394

Khorana KK, Vasyliūnas V, Mauk B, Frank L, Paterson B, Kivelson M, Krupp N, Woch J, Lagg A, Kurth B (2004) The configuration of Jupiter’s magnetosphere. In: Bagenal F, Dowling TE, McKinnon WB (eds) Jupiter: the planet, satellites and magnetosphere. Cambridge University Press, Cambridge, pp 593–616

Kiely A (2004) Selecting the Golomb Parameter in Rice Coding. IPN Progress Report 42-159. https://ipnpr.jpl.nasa.gov/progress_report/42-159/159E.pdf

Kim TK, Ebert RW, Valek PW, Allegrini F, McComas DJ, Bagenal F, et al (2020) Survey of ion properties in Jupiter’s plasma sheet: Juno JADE-I observations. J Geophys Res Space Phys 125:e2019JA027696. https://doi.org/10.1029/2019JA027696

Kimura T, Cecconi B, Zarka P, Kasaba Y, Tsuchiya F, Misawa H, Morioka A (2012) Polarization and direction of arrival of Jovian quasi-periodic bursts observed by Cassini. J Geophys Res 117:A11209

Kintner PM, et al (1987) Detection of spatial density irregularities with the viking plasma wave interferometer. Geophys Res Lett 14(4):467–470. https://doi.org/10.1029/GL014i004p00467

Kitamura N, et al (2018) Direct measurements of two-way wave-particle energy transfer in a collisionless space plasma. Science 361:1000–1003. https://doi.org/10.1126/science.aap8730

Kivelson MG, Southwood DJ (2005) Dynamical consequences of two modes of centrifugal instability in Jupiter’s outer magnetosphere. J Geophys Res Space Phys 110:A12209

Kivelson MG, Khurana KK, Russell CT, et al (1996) Discovery of Ganymede’s magnetic field by the Galileo spacecraft. Nature 384:537–541. https://doi.org/10.1038/384537a0

Kivelson MG, Warnecke J, Bennett L, Joy S, Khurana KK, Linker JA, Russell CT, Walker RJ, Polanskey C (1998) Ganymede’s magnetosphere: magnetometer overview. J Geophys Res 103(E9):19963–19972
Kivelson MG, Khurana KK, Stevenson DJ, Bennett L, Joy S, Russell CT, Walker RJ, Zimmer C, Polanskey C (1999) Europa and Callisto: induced or intrinsic fields in a periodically varying plasma environment. J Geophys Res 104(A3):4609–4625. https://doi.org/10.1029/1998JA900095

Kivelson MG, Khurana KK, Russell CT, Volwerk M, Walker RJ, Zimmer C (2000) Galileo magnetometer measurements: a stronger case for a subsurface ocean at Europa. Science 289:1340–1343. https://doi.org/10.1126/science.289.5483.1340

Kivelson MG, Khurana KK, Volwerk M (2002) The permanent and inductive magnetic moments of Ganymede. Icarus 157(2):507–522. https://doi.org/10.1006/icar.2002.6834

Kivelson MG, Bagenal F, Kurth WS, Neubauer FM, Paranicas C, Saur J (2004) Magnetospheric interactions with satellites. In: Bagenal F, Dowling TE, McKinnon WB (eds) Jupiter: the planet, satellites and magnetosphere. Cambridge University Press, Cambridge, pp 513–536

Kivelson MG, Khurana KK, Volwerk M (2009) In: Pappalardo RT, McKinnon WB, Khurana KK (eds) Europa. University of Arizona Press, Tucson, pp 545–570

Kliore AJ (1998) Satellite atmospheres and magnetospheres. In: Andersen J (ed) Highlights of astronomy. International astronomical union / union astronomique internationale, vol 11B. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4778-1_138

Kliore AJ, Hinson DP, Flasar FM, Nagy AF, Cravens TE (1997) The ionosphere of Europa from Galileo radio occultations. Science 277(5324):355–358. https://doi.org/10.1126/science.277.5324.355

Kliore AJ, Anabtawi A, Herrera RG, Asmar SW, Nagy AF, Hinson DP, Flasar FM (2002) Ionosphere of Callisto from Galileo radio occultation observations. J Geophys Res 107(A11):1407. https://doi.org/10.1029/2002JA009365

Knight S (1973) Parallel electric fields. Planet Space Sci 21:741–750. https://doi.org/10.1016/0032-0633(73)90093-7

Kolmašová I, Imai M, Santolík O, Kurth WS, Hospodarsky GB, Gurnett DA, Connerney JEP, Bolton S (2018) Discovery of rapid whistlers close to Jupiter implying lightning rates similar to those on Earth. Nat Astron 2:544–548. https://doi.org/10.1038/s41550-018-0442-z

Kolmašová I, Santolík O, Imai M, et al (2023) Lightning at Jupiter pulsates in a similar rhythm as in-cloud lightning at Earth. Nat Commun 14:2707. https://doi.org/10.1038/s41467-023-38351-6

Kotsiaros S, Connerney JEP, Clark G, et al (2019) Birkeland currents in Jupiter's magnetosphere observed by the polar-orbiting Juno spacecraft. Nat Astron 3:904–909. https://doi.org/10.1038/s41550-019-0819-7

Kriegel H, Simon S, Motschmann U, Saur J, Neubauer FM, Persoon AM, Dougherty MK, Gurnett DA (2011) Influence of negatively charged plume grains on the structure of Enceladus' Alfvén wings: hybrid simulations versus Cassini magnetometer data. J Geophys Res 116:A10223. https://doi.org/10.1029/2011JA016842

Krivov AV, Krüger H, Grün E, Thiessenhusen K-U, Hamilton DP (2002) A tenuous dust ring of Jupiter formed by escaping ejecta from the Galilean satellites. J Geophys Res 107:E1. https://doi.org/10.1029/2000JE001434

Krüger H, et al (1999) Analysis of the sensor characteristics of the Galileo dust detector with collimated Jovian dust stream particles. Planet Space Sci 47:1015–1028. https://doi.org/10.1016/S0032-0633(99)00027-6

Krüger H, Horányi M, Grün E (2003) Jovian dust streams: probes of the Io plasma torus. Geophys Res Lett 30:1058. https://doi.org/10.1029/2002GL015920

Krupp N, Roussos E, Kollmann P, Paranicas C, Mitchell DG, Krimigis SM, Rymer A, Jones GH, Arridge CS, Armstrong TP, Khurana KK (2012) The Cassini Enceladus encounters 2005–2010 in the view of energetic electron measurements. Icarus 218(1):433–447. https://doi.org/10.1016/j.icarus.2011.12.018

Kumamoto A, Kasaba Y, Tsuchiya F, Misawa H, Kita H, Puccio W, Kobayashi T (2018) Feasibility of the exploration of the subsurface structures of Jupiter's icy moons by interference of Jovian hectometric and decametric radiation, in Planetary Radio Emissions VIII. ISBN 978-3-7001-8263-4 or ISBN 978-3-7001-8392-1, Online Edition https://doi.org/10.1553/PRE8

Kurita S, Miyoshi Y, Cully CM, Angelopoulos V, Le Contel O, Hikishima M, Misawa H (2014) Observational evidence of electron pitch angle scattering driven by ECH waves. Geophys Res Lett 41:8076–8080. https://doi.org/10.1002/2014GL061927

Kurth WS, Gurnett DA, Roux A, Bolton SJ (1997) Ganymede: a new radio source. Geophys Res Lett 24(17):2167–2170. https://doi.org/10.1029/97GL02249

Kurth WS, Gurnett DA, Persoon AM, Roux A, Bolton SJ, Alexander CJ (2001) The plasma wave environment of Europa. Planet Space Sci 49(3–4):345–363. https://doi.org/10.1016/S0032-0633(00)00156-2

Kurth WS, Averkamp TF, Gurnett DA, Wang Z (2006) Cassini RPWS observations of dust in Saturn's E Ring. Planet Space Sci 54(9–10):988–998. https://doi.org/10.1016/j.pss.2006.05.011

Kurth WS, Sulaiman AH, Hospodarsky GB, Menietti JD, Mauk BH, Clark G, et al (2022) Juno plasma wave observations at Ganymede. Geophys Res Lett 49:e2022GL098591. https://doi.org/10.1029/2022GL098591
Kurth WS, Wilkinson DR, Hospodarsky GB, Santolik O, Averkamp TF, Sulaiman AH, Menietti JD, Connerney JEP, Allegrini F, Mauk BH, Bolton SJ (2023) Juno plasma wave observations at Europa. Geophys Res Lett 50:e2023GL105775. https://doi.org/10.1029/2023GL105775

LaBelle J, Kintner PM, Kelley MC (1986) Interferometric phase velocity measurements in the auroral electrojet. Planet Space Sci 34(12):1285-1297. https://doi.org/10.1016/0032-0633(86)90065-6

Lamy L, Colomban L, Zarka P, Prangé R, Marques MS, Louis C, Kurth W, Cecconi B, Girard J, Griessmeier J-M, Yerin S (2022) Determining the beaming of Io decametric emissions: a remote diagnostic to probe the Io-Jupiter interaction. J Geophys Res 127:e2021JA030160. https://doi.org/10.1029/2021JA030160

Lamy L, Duchêne A, Mauduit E, Zarka P, Yerin S, Louis C, Griessmeier J-M, Girard J, Theureau G (2023) Probing Jupiter-satellite interactions from the beaming of their decametric emissions: the case of Europa and Ganymede. Louis CK, Jackman CM, Fischer G, Sulaiman AH, Zucca P (eds) Dublin institute for advanced studies, planetary, solar and heliospheric radio emissions IX. https://doi.org/10.25546/103097

Larsson AL, Wahlund J-E (2004) Low-temperature coatings for instruments on the BepiColombo mission to Mercury. Swedish Institute of Space Physics, IRF-report

Leblanc Y, Rubio M (1982) A narrow-band splitting at the Jovian decametric cutoff frequency. Astron Astrophys 111(2):284-294

Leblanc F, Oza AV, Leclercq L, Schmidt C, Cassidy T, Modolo R, Chaufray JY, Johnson RE (2017) On the orbital variability of Ganymede's atmosphere. Icarus 293:185-198. https://doi.org/10.1016/j.icarus.2017.04.025

Leblanc F, Roth L, Chaufray JY, Modolo R, Galand M, Ivchenko N, Carnielli G, Baskevitch C, Oza A, Werner ALE (2023) Ganymede's atmosphere as constrained by HST/STIS observations. Icarus 399:115557. https://doi.org/10.1016/j.icarus.2023.115557

Lecacheux A (1988) Polarization aspects from planetary radio emissions: In: Rucker HO, Bauer SJ, Pedersen BM (eds) Planetary radio emissions II. Austrian Acad. Sci. Press, Vienna, pp 299-314

Lecacheux A, Boischot A, Boudjada MY, Dulk GA (1991) Spectra and complete polarization state of two, Io-related, radio storms from Jupiter. Astron Astrophys 251(1):339-348

Leclercq L, Modolo R, Leblanc F, Hess S, Mancini M (2016) 3D magnetospheric parallel hybrid multi-grid method applied to planet-plasma interactions. J Comput Phys 309:295-313. https://doi.org/10.1016/j.jcp.2016.01.005

Leisner JS, Hospodarsky GB, Gurnett DA (2013) Enceladus auroral hiss observations: implications for electron beam locations. J Geophys Res Space Phys 118:160-166. https://doi.org/10.1029/2012JA018213

Li J, Gudipati MS, Yung YL (2020) The influence of Europa's plumes on its atmosphere and ionosphere. Icarus 352:113999. https://doi.org/10.1016/j.icarus.2020.113999

Lindkvist J, Holmström M, Khurana KK, Fatemi S, Barabash S (2015) Callisto plasma interactions: hybrid modeling including induction by a subsurface ocean. J Geophys Res Space Phys 120:4877-4889. https://doi.org/10.1002/2015JA021212

Lindkvist P-A, Marklund GT (1990) A statistical study of high-altitude electric fields measured on the viking satellite. J Geophys Res 95(A5):5867-5876. https://doi.org/10.1029/JA095iA05p05867

Liu X, Schmidt J (2019) Dust in the Jupiter system outside the rings. Astrodynamics 3:17-29. https://doi.org/10.1007/s42064-018-0031-z

Louarn P, Wahlund J-E, Chust T, de Feraudy H, Roux A, Holback B, Dovner PO, Eriksson AI, Holmgren G (1994) Observation of kinetic Alfvén waves by the FREJA spacecraft. Geophys Res Lett 21(17):1847-1850. https://doi.org/10.1029/94GL00882

Louarn P, Paranicas CP, Kurth WS (2014) Global magnetodisk disturbances and energetic particle injections at Jupiter. J Geophys Res Space Phys 119:4495-4511. https://doi.org/10.1002/2014JA019846

Louarn P, André N, Jackman CM, Kasahara S, Kronberg EA, Vogt MF (2015) Magnetic reconnection and associated transient phenomena within the magnetospheres of Jupiter and Saturn. Space Sci Rev 187:181-227. https://doi.org/10.1007/s11214-014-0047-5

Louarn P, et al (2017) Generation of the Jovian hectometric radiation: first lessons from Juno. Geophys Res Lett 44:4439-4446. https://doi.org/10.1002/2017GL072923

Louis CK, Lamy L, Zarka P, Cecconi B, Hess SLG (2017) Detection of Jupiter decametric emissions controlled by Europa and Ganymede with Voyager/PRA and Cassini/RPWS. J Geophys Res 122:9228-9247. https://doi.org/10.1002/2016JA023779

Louis CK, Hess SLG, Cecconi B, Zarka P, Lamy L, Aicardi S, Loh A (2019a) ExPRES: an exoplanetary and planetary radio emissions simulator. Astron Astrophys 627:A30. https://doi.org/10.1051/0004-6361/201935161

Louis CK, Prangé R, Lamy L, Zarka P, Imai M, Kurth WS, Connerney JEP (2019b) Jovian auroral radio sources detected in situ by Juno/Waves: comparisons with model auroral ovals and simultaneous HST FUV images. Geophys Res Lett 46. https://doi.org/10.1029/2019GL084799

Louis CK, Zarka P, Dabidin K, Lampson P-A, Magalhaes FP, Boudouma A, Marques MS, Cecconi B (2021) Latitudinal beaming of Jupiter's radio emissions from Juno/waves flux density measurements. J Geophys Res 126(10):e29435. https://doi.org/10.1029/2021JA029435
Louis CK, Jackman CM, Hospodarsky G, O'Kane Hackett A, Devon-Hurley E, Zarka P, et al (2023) Effect of a magnetospheric compression on Jovian radio emissions: in situ case study using Juno data. J Geophys Res Space Phys 128:e2022JA031155. https://doi.org/10.1029/2022JA031155

Lysak RL (2023) Kinetic Alfvén waves and auroral particle acceleration: a review. Rev Mod Plasma Phys 7(1):6. https://doi.org/10.1007/s41614-022-00111-2

Lysak RL, Lotko W (1996) On the kinetic dispersion relation for shear Alfvén waves. J Geophys Res 101(A3):5085–5094. https://doi.org/10.1029/95JA03712

Lysak RL, Echim MM, Karlsson T, Marghitu O, Rankin R, Song Y, Watanabe T (2020) Quiet, discrete auroral arcs: acceleration mechanisms. Space Sci Rev 216:1–31. https://doi.org/10.1007/s11214-020-00715-5

Lysak RL, Song Y, Elliott S, Kurth W, Sulaiman AH, Gershman D (2021) The Jovian ionosphere Alfvén resonator and auroral particle acceleration. J Geophys Res Space Phys 126:e2021JA029886. https://doi.org/10.1029/2021JA029886

MacDowall RJ, Kaiser ML, Desch MD, Farrell WM, Hess RA, Stone RG (1993) Quasiperiodic Jovian radio bursts: observations from the Ulysses radio and plasma wave experiment. Planet Space Sci 41(11/12):1059–1072

Manners H, Masters A (2020) The global distribution of ultralow-frequency waves in Jupiter's magnetosphere. J Geophys Res Space Phys 125:e2020JA028345. https://doi.org/10.1029/2020JA028345

Marklund G, Ivchenko N, Karlsson T, et al (2001) Temporal evolution of the electric field accelerating electrons away from the auroral ionosphere. Nature 414:724–727. https://doi.org/10.1038/414724a

Marklund GT, et al (2011) Evolution in space and time of the quasi-static acceleration potential of inverted-V aurora and its interaction with Alfvénic boundary processes. J Geophys Res 116:A00K13. https://doi.org/10.1029/2011JA016537

Marques MS, Zarka P, Echer E, Ryabov VB, Alves MV, Denis L, Coffre A (2017) Statistical analysis of 26 years of observations of decametric radio emissions from Jupiter. Astron Astrophys 604:A17. https://doi.org/10.1051/0004-6361/20160025

Marzok A, Schlegel S, Saur J, Roth L, Grodent D, Strobel DF, Retherford KD (2022) Mapping the brightness of Ganymede's ultraviolet aurora using Hubble Space Telescope observations. J Geophys Res, Planets 127:e2022JE007256. https://doi.org/10.1029/2022JE007256

Masters A, Modolo R, Roussos E et al. (2024) Magnetosphere and plasma cience with the Jupiter icy moons explorer. Space Sci Rev

Mauduit E, Zarka P, Lamy L, Hess SLG (2023) Drifting discrete Jovian radio bursts reveal acceleration processes related to Ganymede and the main aurora. Nat Commun. https://doi.org/10.1038/s41467-023-41617-8

Mauk BH, Mitchell DG, Krimigis SM, Roelof EC, Paranicas CP (2003) Energetic neutral atoms from a trans-Europa gas torus at Jupiter. Nature 421(6926):920–922. https://doi.org/10.1038/nature01431

Mauk BH, Clark G, Gladstone GR, Kotsiaros S, Adriani A, Allegrini F, et al (2020) Energetic particles and acceleration regions over Jupiter's polar cap and main aurora: a broad overview. J Geophys Res Space Phys 125:e2019JA027699. https://doi.org/10.1029/2019JA027699

McGrath MA, Hansen CJ, Hendrix AR (2009) Observations of Europa's tenuous atmosphere. In: Pappalardo RT, McKinnon WB, Khurana KK (eds) Europa. University of Arizona Press, Tucson, pp 485–506

McGrath MA, Jia X, Retherford K, Feldman PD, Strobel DF, Saur J (2013) Aurora on Ganymede. J Geophys Res Space Phys 118:2043–2054. https://doi.org/10.1002/jgra.50122

McNutt R, Belcher J, Sullivan J, et al (1979) Departure from rigid co-rotation of plasma in Jupiter's dayside magnetosphere. Nature 280:803. https://doi.org/10.1038/280803a0

Meyer-Vernet N, Lecacheux A, Pedersen BM (1996) Constraints on Saturn's E Ring from the Voyager 1 radio astronomy instrument. Icarus 123(1):113–128. https://doi.org/10.1006/icar.1996.0145

Meyer-Vernet N, Maksimovic M, Czechowski A, et al (2009) Dust detection by the wave instrument on STEREO: nanoparticles picked up by the solar wind? Sol Phys 256:463–474. https://doi.org/10.1007/s11207-009-9349-2

Modolo R, et al (2018) The LatHyS database for planetary plasma environment investigations: overview and a case study of data/model comparisons. Planet Space Sci 150:13–21. https://doi.org/10.1016/j.pss.2017.02.015

Molyneux PM, Nichols JD, Bannister NP, Bunce EJ, Clarke JT, Cowley SWH, et al (2018) Hubble Space Telescope observations of variations in Ganymede's oxygen atmosphere and aurora. J Geophys Res Space Phys 123:3777–3793. https://doi.org/10.1029/2018JA025243

Morioka A, Nozawa H, Misawa H, Tsuchiya F, Miyoshi Y, Kimura T, Kurth W (2006) Rotationally driven quasi-periodic radio emissions in the Jovian magnetosphere. J Geophys Res 111:A04223. https://doi.org/10.1029/2005JA011563

Morooka MW, André M, Wahlund J-E, Buchert SC, Fazakerley AN, Winningham JD, Re'me H, Dandouras I, Lavraud B, Balogh A, Igenbergs K (2004) Cluster observations of ULF waves with pulsating electron beams above the high latitude dusk-side auroral region. Geophys Res Lett 31:L05804. https://doi.org/10.1029/2003GL017714
Morooka MW, Modolo R, Wahlund J-E, André M, Eriksson AI, Persoon AM, Gurnett DA, Kurth WS, Coates AJ, Lewis GR, Khurana KK, Dougherty M (2009) The electron density of Saturn's magnetosphere. Ann Geophys 27:2971. http://www.ann-geophys.net/27/2971/2009/

Morooka MW, Wahlund J-E, Eriksson AI, Farrell WM, Gurnett DA, Kurth WS, Persoon AM, Shafiq M, André M, Holmberg MKG (2011) Dusty plasma in the vicinity of Enceladus. J Geophys Res 116:A12221. https://doi.org/10.1029/2011JA017038

Mott-Smith HM, Langmuir I (1926) The theory of collectors in gaseous discharges. Phys Rev 28:727. https://doi.org/10.1103/PhysRev.28.727

Mottez F, Hess SLG, Zarka P (2010) Explanation of dominant oblique radio emission at Jupiter and comparison to the Terrestrial case. Planet Space Sci 58:1414-1422

Mozer FS, Bruston P (1967) Electric field measurements in the auroral ionosphere. J Geophys Res 72(3):1109-1114. https://doi.org/10.1029/JZ072i003p01109

Mozer FS, Kletzing CA (1998) Direct observation of large, quasi-static, parallel electric fields in the auroral acceleration region. Geophys Res Lett 25(10):1629-1632. https://doi.org/10.1029/98GL00849

Mozer FS, Carlson CW, Hudson MK, Torbert RB, Parady B, Yatteau J, Kelley MC (1977) Observations of paired electrostatic shocks in the polar magnetosphere. Phys Rev Lett 38:6. https://doi.org/10.1103/PhysRevLett.38.292

Mozer FS, et al (2022) Core electron heating by triggered ion acoustic waves in the solar wind. Astrophys J Lett 927:L15. https://doi.org/10.3847/2041-8213/ac5520

Neubauer F (1980) Nonlinear standing Alfvén wave current system at Io: theory. J Geophys Res 85(A3):1171-1178. https://doi.org/10.1029/JA085iA03p01171

Neubauer FM (1998) The sub-Alfvénic interaction of the Galilean satellites with the Jovian magnetosphere. J Geophys Res 103(E9):19843-19866. https://doi.org/10.1029/97JE03370

Neubauer FM (1999) Alfvén wings and electromagnetic induction in the interiors: Europa and Callisto. J Geophys Res 104(A12):28671-28684. https://doi.org/10.1029/1999JA900217

Newell PT, Sotirelis T, Wing S (2009) Diffuse, monoenergetic, and broadband aurora: the global precipitation budget. J Geophys Res 114:A09207. https://doi.org/10.1029/2009JA014326

Ni B, Thorne RM, Horne RB, Meredith NP, Shprits YY, Chen L, Li W (2011) Resonant scattering of plasma sheet electrons leading to diffuse auroral precipitation: 1. Evaluation for electrostatic electron cyclotron harmonic waves. J Geophys Res 116:A04218. https://doi.org/10.1029/2010JA016232

Nichols JD (2011) Magnetosphere-ionosphere coupling in Jupiter's middle magnetosphere: computations including a self-consistent current sheet magnetic field model. J Geophys Res 116:A10232. https://doi.org/10.1029/2011JA016922

Nimmo F, Schenk P (2008) Stereo and photoclinometric comparisons and topographic roughness of Europa. Lunar Planet Sci

Nishimura Y, Donovan EF, Angelopoulos V, Nishitani N (2020) Dynamics of auroral precipitation boundaries associated with STEVE and SAID. J Geophys Res Space Phys 125:e2020JA028067. https://doi.org/10.1029/2020JA028067

Odelstad E, Stenberg-Wieser G, Wieser M, Eriksson AI, Nilsson H, Johansson FL (2017) Measurements of the electrostatic potential of Rosetta at comet 67P. Mon Not R Astron Soc 469(Suppl_2):S568-S581. https://doi.org/10.1093/mnras/stx2232

Ono T, Kumamoto A, Kasahara Y, Yamaguchi Y, Yamaji A, Kobayashi T, Oshigami S, Nakagawa H, Goto Y, Hashimoto K, Omura Y, Imachi T, Matsumoto H, Oya H (2010) The lunar radar sounder (LRS) onboard the KAGUYA (SELENE) spacecraft. Space Sci Rev 154:145-192. https://doi.org/10.1007/s11214-010-9673-8

Ossowski M, Borys M, Palma P, Wisniewski L, Tokarz M, Kuciński T, Ryszawa E, Bochra K, Duda M, Grygorczuk J (2021) Development of deployable RWI and LP-PWI mechanisms for JUICE mission – quality and product assurance aspects. In: European conference on spacecraft structures, materials and environmental. Testing (ECSSMET 2021)

Panchenko M, Rucker HO, Kaiser ML, St. Cyr OC, Bougeret J-L, Goetz K, Bale SD (2010) New periodicity in Jovian decametric radio emission. Geophys Res Lett 37:L05106. https://doi.org/10.1029/2010GL042488

Panchenko M, Rucker HO, Farrell WM (2013) Periodic bursts of Jovian non-Io decametric radio emission. Planet Space Sci 77:3-11. https://doi.org/10.1016/j.pss.2012.08.015

Panchenko M, Rošker S, Rucker HO, Brazhenko A, Zarka P, Litvinenko G, Shaposhnikov VE, Konovalenko AA, Melnik V, Franzuzenko AV, Schiemel J (2018) Zebra pattern in decametric radio emission of Jupiter. Astron Astrophys 610:A69

Paschmann G, Haaland S, Treumann R (eds) (2003) Auroral plasma physics. Space sciences series of ISSI, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1086-3

Persoon AM, Gurnett DA, Peterson WK, Waite JH, Burch JL, Green JL (1988) Electron density depletions in the nightside auroral zone. J Geophys Res 93(A3):1871-1895. https://doi.org/10.1029/JA093iA03p01871
Petkaki P, Dougherty MK (2001) Waves close to the crossover frequency in the Jovian middle magnetosphere. Geophys Res Lett 28(2):211–214. https://doi.org/10.1029/2000GL012029

Polyakov SV (1976) On properties of ionospheric Alfvén resonator. In: Symposium KAPG on solar-terrestrial physics. Theses of reports. Part III. Nauka, Moscow, pp 72–73

Pontius DH, Hill TW (2006) Enceladus: a significant plasma source for Saturn’s magnetosphere. J Geophys Res 111:A09214. https://doi.org/10.1029/2006JA011674

Poppe AR, Fatemi S, Khurana KK (2018) Thermal and energetic ion dynamics in Ganymede’s magnetosphere. J Geophys Res Space Phys 123:4614–4637. https://doi.org/10.1029/2018JA025312

Porco CC, Helfenstein P, Thomas PC, Ingersoll AP, Wisdom J, West R, Neukum G, Denk T, Wagner R, Roatsch T, Kieffer S, Turtle E, McEwen A, Johnson TV, Rathbun J, Veverka J, Wilson D, Perry J, Spitale J, Brahic A, Burns JA, DelGenio AD, Dones L, Murray CD, Squyres S (2006) Cassini observes the active south pole of Enceladus. Science 311:1393–1401. https://doi.org/10.1126/science.1123013

Postberg F, Kempf S, Schmidt J, et al (2009) Sodium salts in E-ring ice grains from an ocean below the surface of Enceladus. Nature 459:1098–1101. https://doi.org/10.1038/nature08046

Postberg F, Schmidt J, Hillier J, et al (2011) A salt-water reservoir as the source of a compositionally stratified plume on Enceladus. Nature 474:620–622. https://doi.org/10.1038/nature10175

Postberg F, Khawaja N, Abel B, Choblet G, Glein CR, Gudipati MS, Henderson BL, Hsu HW, Kempf S, Klenner F, Moragas-Klostermeyer G, Magee B, Nölle L, Perry M, Reviol R, Schmidt J, Srama R, Stolz F, Tobie G, Trieloff M, Waite JH (2018) Macromolecular organic compounds from the depths of Enceladus. Nature 558(7711):564–568. https://doi.org/10.1038/s41586-018-0246-4

Postberg F, Sekine Y, Klenner F, et al (2023) Detection of phosphates originating from Enceladus’s ocean. Nature 618:489–493. https://doi.org/10.1038/s41586-023-05987-9

Pryor W, Rymer A, Mitchell D, et al (2011) The auroral footprint of Enceladus on Saturn. Nature 472:331–333. https://doi.org/10.1038/nature09928

Rabia J, Hue V, Szalay JR, André N, Nénon Q, Blanc M, et al (2023) Evidence for non-monotonic and broadband electron distributions in the Europa footprint tail revealed by Juno in situ measurements. Geophys Res Lett 50:e2023GL103131. https://doi.org/10.1029/2023GL103131

Callingham JR, Vedantham HK, Shimwell TW, et al (2021) The population of M dwarfs observed at low radio frequencies. Nat Astron 5:1233–1239

Reiner MJ, Fainberg J, Stone RG, Kaiser ML, Desch MD, Manning R, Zarka P, Pedersen BM (1993) Source characteristics of Jovian narrow-band kilometric radio emissions. J Geophys Res, Planets 98:13163–13176

Reiner M, et al (1995) Elliptically polarized bursty radio emissions from Jupiter. Geophys Res Lett 22:345–348

Rice RF, Yeh P-S, Miller WH (1993) Algorithms for high-speed universal noiseless coding. In: Proceedings of AIAA computing in aerospace, IX, October 19-21, 1993, San Diego, CA. AIAA, Reston. https://doi.org/10.2514/6.1993-4541

Roberts TM, Romero-Wolf A, Bruzzone L, Carrer L, Peters S, Schroeder DM (2021) Conditioning Jovian Burst Signals for Passive Sounding Applications. IEEE Trans Geosci Remote Sens

Romero-Wolf A, Vance S, Maiwald F, Heggy E, Ries P, Liewer K (2015) A passive probe for subsurface oceans and liquid water in Jupiter’s icy moons. Icarus 248:463–477

Roth L (2021) A stable H₂O atmosphere on Europa’s trailing hemisphere from HST images. Geophys Res Lett 48:e2021GL094289. https://doi.org/10.1029/2021GL094289

Roth L, et al (2014a) Transient water vapor at Europa’s south pole. Science 343:171–174. https://doi.org/10.1126/science.124705

Roth L, Retherford KD, Saur J, Strobel DF, Feldman PD, McGrath MA, Nimmo F (2014b) Orbital apocenter is not a sufficient condition for HST/STIS detection of Europa’s water vapor aurora. Proc Natl Acad Sci 111(48):E5123–E5132. https://doi.org/10.1073/pnas.1416671111

Roth L, Smith HT, Yoshioka K, Becker TM, Blöcker A, Cunningham NJ, Ivchenko N, Retherford KD, Saur J, Velez M, Tsuchiya F (2023) Constraints on Europa’s water group torus from HST/COS observations. Planet Sci J 4:87. https://doi.org/10.3847/PSJ/accddd

Sandahl I, Eliasson L, Lundin R (1980) Rocket observations of precipitating electrons over a pulsating aurora. Geophys Res Lett 7:309–312. https://doi.org/10.1029/GL007i005p00309

Sarrailh P, Matéo-Vélez J-C, Hess SLG, Roussel J-F, Thiébault B, Forest J, Payan D (2015) SPIS 5: new modeling capabilities and methods for scientific missions. IEEE Trans Plasma Sci 43(9):2789–2798. https://doi.org/10.1109/TPS.2015.2445384

Sato T (1978) A theory of quiet auroral arcs. J Geophys Res 83(A3):1042–1048. https://doi.org/10.1029/JA083iA03p01042

Saur J, Strobel DF, Neubauer FM (1998) Interaction of the Jovian magnetosphere with Europa: constraints on the neutral atmosphere. J Geophys Res 103(E9):19947–19962. https://doi.org/10.1029/97JE03556
Saur J, Neubauer FM, Schilling N (2007) Hemisphere coupling in Enceladus' asymmetric plasma interaction. J Geophys Res 112:A11209. https://doi.org/10.1029/2007JA012479

Saur J, Neubauer FM, Glassmeier K-H (2010) Induced magnetic fields in Solar System bodies. Space Sci Rev 152:391-421. https://doi.org/10.1007/s11214-009-9581-y

Saur J, Feldman PD, Roth L, Nimmo F, Strobel DF, Retherford KD, Mc Grath MA, Schilling N, Gérard J-C, Grodent D (2011) Hubble Space Telescope/advanced camera for surveys observations of Europa's atmospheric ultraviolet emission at eastern elongation. Astrophys J 738:2. https://doi.org/10.1088/0004-637X/738/2/153

Saur J, et al (2015) The search for a subsurface ocean in Ganymede with Hubble Space Telescope observations of its auroral ovals. J Geophys Res Space Phys 120:1715-1737. https://doi.org/10.1002/2014JA020778

Saur J, Janser S, Schreiner A, Clark G, Mauk BH, Kollman P, et al (2018) Wave-particle interaction of Alfvén waves in Jupiter's magnetosphere: auroral and magnetospheric particle acceleration. J Geophys Res Space Phys 123:9560-9573. https://doi.org/10.1029/2018JA025948

Schroeder DM, Romero-Wolf A, Carrer L, Grima C, Campbell BA, Kofman W, Blankenship DD (2016) Assessing the potential for passive radio sounding of Europa and Ganymede with RIME and REASON. Planet Space Sci 134:52-60

Schukla P, Stenflo L (2000) Generalized dispersive Alfvén waves. J Plasma Phys 64(2):125-130. https://doi.org/10.1017/S0022377800008412

Seyler CE, Clark AE, Bonnell J, Wahlund J-E (1998) Electrostatic broadband ELF wave emission by Alfvén wave breaking. J Geophys Res 103(A4):7027-7041. https://doi.org/10.1029/97JA02297

Shafiq M, Wahlund J-E, Morooka MW, Kurth WS, Farrell WM (2011) Characteristics of the dust-plasma interaction near Enceladus' South Pole. Planet Space Sci 59(1):17-25. https://doi.org/10.1016/j.pss.2010.10.006

Shoji M, Miyoshi Y, Kistler LM, et al (2021) Discovery of proton hill in the phase space during interactions between ions and electromagnetic ion cyclotron waves. Sci Rep 11:13480. https://doi.org/10.1038/s41598-021-92541-0

Shprits YY, Menietti JD, Drozdov AY, et al (2018) Strong whistler mode waves observed in the vicinity of Jupiter's moons. Nat Commun 9:3131. https://doi.org/10.1038/s41467-018-05431-x

Simon S, Saur J, van Treeck SC, Kriegel H, Dougherty MK (2014) Discontinuities in the magnetic field near Enceladus. Geophys Res Lett 41:3359-3366. https://doi.org/10.1002/2014GL060081

Simpson F, Bahr K (2005) Practical magnetotellurics. Cambridge University Press, Cambridge

Smith T, Mitchell DG, Johnson RE, Mauk BH, Smith JE (2019) Europa neutral torus confirmation and characterization based on observations and modeling. Astrophys J 871(1):69. https://doi.org/10.3847/1538-4357/aaed38

Soja RH, Altobelli N, Krüger H, Sterken VJ (2013) Dust environment predictions for the ESA L-class mission JUICE. Planet Space Sci 75:117-128. https://doi.org/10.1016/j.pss.2012.11.010

Soucek J, Přsa D, Kolmasova I, Uhlíř L, Lan R, Santolík O, Krupar V, Kruparova O, Baše J, Maksimovic M, Bale SD, Chust T, Khotyaintsev YuV, Krasnoselskikh V, Kretzschmar M, Lorfèvre E, Plettemeier D, Steller M, Štverák Š, Vaivads A, Vecchio A, Bérard D, Bonnin X (2021) Solar Orbiter radio and plasma waves - time domain sampler: in-flight performance and first results. Astron Astrophys 656:A26. https://doi.org/10.1051/0004-6361/202140948

Spahn F, et al (2006) Cassini dust measurements at Enceladus and implications for the origin of the E Ring. Science 311:1416-1418. https://doi.org/10.1126/science.1121375

Sparks WB, Hand KP, McGrath MA, Bergeron E, Cracraft M, Deustua SE (2016) Probing evidence of plumes on Europa with HST/STIS. Astrophys J 829:2. https://doi.org/10.3847/0004-637X/829/2/121

Spitale JN, Porco CC (2007) Association of the jets of Enceladus with the warmest regions on its south-polar fractures. Nature 449(7163):695-697. https://doi.org/10.1038/nature06217

Stasiewicz K, Bellan P, Chaston C, Kletzing C, Lysak R, Maggs J, Pokhotelov O, Seyler C, Shukla P, Stenflo L, Streltsov A, Wahlund J-E (2000b) Small scale Alfvénic structure in the Aurora. Space Sci Rev 92:423-533. https://doi.org/10.1023/A:1005207202143

Stasiewicz K, Khotyaintsev Y, Berthomier M, Wahlund J-E (2000a) Identification of widespread turbulence of dispersive Alfvén waves. Geophys Res Lett. https://doi.org/10.1029/1999GL010696

Steinbrugge G, Schroeder DM, Haynes MS, Hussmann H, Grima C, Blankenship DD (2018) Assessing the potential for measuring Europa's tidal Love number h2 using radar sounder and topographic imager data. Earth Planet Sci Lett 482:334-341. https://doi.org/10.1016/j.epsl.2017.11.028

Steinvall K, Khotyaintsev YuV, Cozzani G, Vaivads A, Yordanova E, Eriksson AI, Edberg NJT, Maksimovic M, Bale SD, Chust T (2021) Solar wind current sheets and deHoffmann-Teller analysis – first results from Solar Orbiter's DC electric field measurements. Astron Astrophys 656:A9. https://doi.org/10.1051/0004-6361/202140855

Stone RG, et al (1992) Ulysses radio and plasma wave observations in the Jupiter environment. Science 257:1524-1531. https://doi.org/10.1126/science.257.5076.1524
Storey L, Aubry L, Meyer P (1969) In: Measurement techniques in space plasmas - fields. Geophysical monograph series, vol 103, p 155. https://doi.org/10.1029/GM103p0155

Streltsov AV, Karlsson T (2008) Small-scale, localized electromagnetic waves observed by cluster: result of magnetosphere-ionosphere interactions. Geophys Res Lett 35:L22107. https://doi.org/10.1029/2008GL035956

Sulaiman AH, Kurth WS, Hospodarsky GB, Averkamp TF, Ye S-Y, Menietti JD, et al (2018) Enceladus auroral hiss emissions during Cassini's grand finale. Geophys Res Lett 45:7347–7353. https://doi.org/10.1029/2018GL078130

Sulaiman AH, Mauk BH, Szalay JR, Allegrini F, Clark G, Gladstone GR, et al (2022) Jupiter's low-altitude auroral zones: fields, particles, plasma waves, and density depletions. J Geophys Res Space Phys 127:e2022JA030334. https://doi.org/10.1029/2022JA030334

Szalay JR, Allegrini F, Bagenal F, Bolton SJ, Bonfond B, Clark G, et al (2020b) Alfvénic acceleration sustains Ganymede's footprint tail aurora. Geophys Res Lett 47:e2019GL086527. https://doi.org/10.1029/2019GL086527

Szalay JR, Bagenal F, Allegrini F, Bonfond B, Clark G, Connerney JEP, et al (2020a) Proton acceleration by Io's Alfvénic interaction. J Geophys Res Space Phys 125(1):e2019JA027314. https://doi.org/10.1029/2019JA027314

Szalay JR, Smith HT, Zirstein EJ, McComas DJ, Begley LJ, Bagenal F, et al (2022) Water-group pickup ions from Europa-genic neutrals orbiting Jupiter. Geophys Res Lett 49:e2022GL098111. https://doi.org/10.1029/2022GL098111

Tao C, Sahraoui F, Fontaine D, de Patoul J, Chust T, Kasahara S, Retinò A (2015) Properties of Jupiter's magnetospheric turbulence observed by the Galileo spacecraft. J Geophys Res Space Phys 120:2477–2493. https://doi.org/10.1002/2014JA020749

Temerin M, Roth I (1986) Ion heating by waves with frequencies below the ion gyrofrequency. Geophys Res Lett 13(11):1109–1112. https://doi.org/10.1029/GL013i01p01109

Thiessenhusen K-U, Krüger H, Spahn F, Grün E (2000) Dust grains around Jupiter—the observations of the Galileo dust detector. Icarus 144(1):89–98. https://doi.org/10.1006/icar.1999.6277

Tokar RL, Johnson RE, Hill TW, Pontius DH, Kurth WS, Crary FJ, Young DT, Thomsen MF, Reisenfeld DB, Coates AJ, Lewis GR, Sittler EC, Gurnett DA (2006) The interaction of the atmosphere of Enceladus with Saturn's plasma. Science 311(5766):1409–1412. https://doi.org/10.1126/science.1121061

Tokar RL, et al (2008) Cassini detection of water-group pick-up ions in the Enceladus torus. Geophys Res Lett 35:L14202. https://doi.org/10.1029/2008GL034749

Tokar RL, Johnson RE, Thomsen MF, Wilson RJ, Young DT, Crary FJ, Coates AJ, Jones GH, Paty CS (2009) Cassini detection of Enceladus' cold water-group plume ionosphere. Geophys Res Lett 36:L13203. https://doi.org/10.1029/2009GL038923

Toledo-Redondo S, André M, Aunai N, Chappell CR, Dargent J, Fuselier SA, et al (2021) Impacts of ionospheric ions on magnetic reconnection and Earth's magnetosphere dynamics. Rev Geophys 59:e2020RG000707. https://doi.org/10.1029/2020RG000707

Tosi F, Roatsch T, Galli A, et al (2024) Characterization of the surfaces and near-surface atmospheres of Ganymede, Europa and Callisto by JUICE. Space Sci Rev 220:59. https://doi.org/10.1007/s11214-024-01089-8

Tóth G, Jia X, Markidis S, Peng IB, Chen Y, Daldorff LKS, Tenishev VM, Borovikov D, Haiducek JD, Gombosi TI, et al (2016) Extended magnetohydrodynamics with embedded particle-in-cell simulation of Ganymede's magnetosphere. J Geophys Res Space Phys 121:1273–1293. https://doi.org/10.1002/2015JA021997

Tyler RH, Boyer TP, Minami T, et al (2017) Electrical conductivity of the global ocean. Earth Planets Space 69:156. https://doi.org/10.1186/s40623-017-0739-7

Valek PW, Waite JH, Allegrini F, Ebert RW, Bagenal F, Bolton SJ, et al (2022) In situ ion composition observations of Ganymede's outflowing ionosphere. Geophys Res Lett 49:e2022GL00281. https://doi.org/10.1029/2022GL00281

Van Hoolst T, Tobie G, Vallat C, et al (2024) Geophysical characterization of the interiors of Ganymede, Callisto and Europa by ESA's JUpiter ICy moons Explorer. Space Sci Rev 220:54. https://doi.org/10.1007/s11214-024-01085-y

Veszelei M, Veszelei E (1993) Optical properties and equilibrium temperatures of titanium-nitride-and graphite-coated Langmuir probes for space application. Thin Solid Films 236(1–2):46–50. https://doi.org/10.1016/0040-6090(93)90640-B

Viberg H, Khotyaintsev YuV, Vaivads A, André M, Pickett JS (2013) Mapping HF waves in the reconnection diffusion region. Geophys Res Lett 40:1032–1037. https://doi.org/10.1002/grl.50227

Vines SK, Fuselier SA, Trattner KJ, Burch JL, Allen RC, Petrinec SM, Russell CT (2017) Magnetospheric ion evolution across the low-latitude boundary layer separatrix. J Geophys Res Space Phys 122:10,247–10,262. https://doi.org/10.1002/2017JA024061