esa-sceva/satcom-chunk-collection huggingface dataset:
# Feasibility, Design, and Deployment Requirements of TCR for Bistatic SAR radiometric Calibration
## 7 Conclusions  
The RCS characteristics and the requirements of radiometric calibration for bistatic SAR were analyzed based on the electromagnetic simulations. We concluded that the TCR could be used as a bistatic calibration target for relatively small bistatic angles (less than 6\({}^{\circ}\)). TCR are generally considered not suitable for bistatic SAR calibration with large bistatic angles, but we have proposed that if we consider the TCR boresight changes with the bistatic angle, the bistatic angle can be extended to 20\({}^{\circ}\). Both of these two conditions have their own advantages and disadvantages. If the change of TCR boresight with the bistatic angle is not considered, we just place it according to the TCR boresight of the monostatic calibration; however, it is not suitable for large bistatic angles (more than 6\({}^{\circ}\)). In addition, the TCR was considered a good calibration target at a bistatic angle of less than 20\({}^{\circ}\), but we need to know the optimum boresight in advance and align the TCR boresight with respect to the SAR antenna boresight during the deployment. To further verify the feasibility, bistatic SAR image quality and point target energy were analyzed. The importance of the study lies in that we can make full use of the advantages of the TCR, and then solve the problem of applicability and a design that is suitable TCR for bistatic radiometric calibration. Furthermore, the simulation results support that attention should be paid to ensure orthogonality between the three plates, interleg dimensions, and alignment, which will have reference value and guidance significance for the design and utilization of TCR RCS in bistatic SAR calibration.  
[PERSON] played the leading role in preparing this article. [PERSON] performed the electromagnetic simulations and analyzed the data. [PERSON] contributed to the structure and revision of this article and provided insightful comments and suggestions. [PERSON] provided valuable suggestions and revised the manuscript.  
This research work was partly supported by the NSFC (the National Natural Science Foundation of China, No. 61771453) and Equipment Development Department pre-research fund No. 6140416010202.  
Thanks go to [PERSON] for providing some plotting supports. The authors would like to thank the anonymous reviewers for their meticulous work in enhancing the quality of this paper.  
The authors declare no conflict of interest.
# Low Discrepancy Sparse Phased Array Antennas
## 2 Sampling Points on a Planar Aperture
### Low Discrepancy Sampling Approaches
#### 2.2.4 Poisson Disk Sampling  
Poisson disk sampling produces points, \(X=\{x_{i}\}\), from a given domain, \(D\), in \(N\)-dimensional space, that are tightly packed, but no closer than a specified minimum distance \(r\). Here \(N\) is the number of elements in the array. The samples are at least a minimum distance apart, satisfying an empty disk criterion, i.e.,  
\[\forall x_{i},x_{j}\in X,x_{i}\
eq x_{j}:\|x_{i}-x_{j}\|\geq r. \tag{12}\]  
The maximal condition requires that the disks are simultaneously closely packed together, in the sense that the sample disks cover the whole domain. Mathematically this is given by  
\[\forall x\in D,\exists x_{i}\in X:\|x-x_{i}\|<r. \tag{13}\]The Poisson distribution also possesses bias-free property which means that the expected number of sample points inside any subdomain, \(\Omega\), is proportional to the area of the subdomain. This is achieved by ensuring that the probability of selecting a point for the next sample is equal to the probability of selecting any other point, provided these points are not already inside some prior sample's disk, i.e.,  
\[\forall x_{i}\in X,\ \forall\Omega\subset D_{i}:P(x_{i}\in\Omega)=\frac{\text{ Area}(\Omega)}{\text{Area}(D_{i})}. \tag{14}\]  
Multiple algorithms have been developed to implement this technique, and the reader is referred to [49; 50] for detailed surveys of implementing Poisson sampling methods. Finally, we note that since this approach requires one to specify the total number of elements, it is not hierarchical.
# Reactive Balance Control for Legged Robots under Visco-Elastic Contacts
## 1 Introduction  
### Problem Overview  
Balance control of legged robots is a fundamental problem in robotics and is at the heart of numerous recent publications in the literature [1]. In this task, depending on whether the contact between the robot and the environment is rigid or soft, the robot will behave differently. However, for the sake of simplicity, a large part of studies has focused on the problem of controlling the balance of a _rigid_ robot in contact with a _rigid_ environment [2; 3; 4; 5; 6; 7]. In this scenario, theoretically, the contact forces between the robot and the environment can be modified instantaneously. This is no longer possible if the environment is visco-elastic, or, equivalently, if a _visco-elastic element_ is located between the robot actuators and the contact points, as in many legged robots which include soft elements at the ankles or the feet [7; 8; 9; 10]. These compliant elements are extremely useful: they absorb impact during walking/running, protect the mechanical structure, tend to improve the quality of force measurements, and can make walking more efficient [10]. Moreover, the assumption of rigid contact is always an approximation because in the real world all contacts are visco-elastic up to a certain extent. In the presence of elasticity, the contact forces cannot be instantaneously modified, but their derivative--either of first or second order--can be modified depending on the contact damping (as detailed in Section 2). Despite the popularity of visco-elastic elements, balancing on visco-elastic contacts is still an open problem. This question is at the heart of the paper. It is addressed through the introduction of two new compliant controllers and a comparative study with existing strategies.
## 4 Test Scenarios  
Different scenarios with and without jamming are explored to investigate GNSS vulnerabilities in the maritime environment. When the signals are jammed, different  
Figure 5: Concept illustration of a resilient MFMC receiver.  
front-ends react differently depending on the Jamming-to-Signal power ratio ((J/S). The Automatic Gain Control (AGC) of the front-end is the first line of defense against the jamming or interference [28; 29]. Some front-ends may have a light interference mitigation feature built in. Since jamming signal raises the noise level in the system, it has a direct impact on the C/N\({}_{0}\) of the received GNSS signals.  
The impact of jamming on all tracked satellites in the impacted frequency band is nearly identical for a given constellation. In the following experiments, the rapid C/N\({}_{0}\) degradation is observed in the affected frequency bands due to deliberate jamming, where very little or no C/N\({}_{0}\) variation is observed in the non-affected bands. Four different scenarios are considered to analyze the performance of a resilient MFMC receiver in a maritime environment:  
* Scenario I: Nominal maritime navigation without the presence of jamming.
* Scenario II: Maritime navigation under the influence of jamming on GNSS L1/E1/B1 signal.
* Scenario III: Maritime navigation under the influence of jamming on GNSS L5/E5a/E5b signal.
* Scenario IV: Maritime Navigation Under the Influence of Jamming on Lower and Upper L-bands.
# Ionospheric Error Models for Satellite-Based Navigation--Paving the Road towards LEO-PNT Solutions
## 2 Related Work
### IGS Model and Database  
The IGS is an organization that has a goal of providing high-quality GNSS data and products. It depends on a collaborative effort of over 200 independent agencies, research facilities, and universities worldwide to provide high-precision data for research purposes. Since its launch in 1994, the IGS has continuously provided an open-access time series of various products with the help of a global network of 450 permanent stations. Such products include clocks and orbits for GNSS and ionospheric and tropospheric products. Several working groups in the IGS are responsible for delivering these products [7].  
The Ionosphere Working Group (IWG) is one of these groups tasked with providing ionospheric products. It combines VTEC maps generated by various stations around the world into Global Ionospheric Maps (GIMs), which manifest a global VTEC content of the ionosphere. These maps are generated by analyzing dual-frequency measurements taken by their GNSS stations. According to [39], in 2021, there were eight such stations around the world, called analysis centers. In order to provide GIMs in a standardized format that is easy to exchange, IONosphere map EXchange format (IONEX) has been developed [7].  
Currently, the GIMs in IONEX format provided by the IGS come in different types with different latencies depending on the data needed to compute the products:  
* Final GIMs (11 days);
* Rapid GIMs [39; 47], which are lower-accuracy rapid solutions (<24 h);
* A predicted solution (available 1-2 days in advance).  
These maps contain, among other information, TEC maps for each epoch (see an explanation in Figure 2, where \(\lambda_{i}\) stands for longitudes and \(\varphi_{i}\) stand for latitudes at point \(i\)). These maps are captured at a discrete time \(t_{i}\) every 2 h for 24 h from 00:00 h to 00:00 h the next day, yielding a total of 13 ionospheric maps, each containing TEC values for latitudes \(\varphi_{i}\) between \(87.5^{\circ}\) and \(-87.5^{\circ}\) with a spatial resolution of \(2.5^{\circ}\) and longitudes \(\lambda_{k}\) between \(-180^{\circ}\) and \(180^{\circ}\) with a spatial resolution of \(5^{\circ}\)[48].  
Our proposed IAMM model is based on the IONEX data in the IGS database, as explained later in Section 3. Since our model is based on IGS, we did not include IGS as an additional benchmark in our validation results because we believed that this would not bring sufficient added value in the validation process. Instead, we used two external models unrelated to our model to validate the findings (namely, Klobuchar and IRI).
# An Introduction of a Modular Framework for Securing 5G Networks and Beyond
## 4 An Integrated Security Solution
### Connection of Different Levels of NSS Model in 5G Enabled D2D System  
When a user requests network access using a UE, the closest SEAF will start the primary authentication procedure. In [32], the procedure for the UE to access the network and services is covered. According to the following descriptions, the security model aims to provide three secure connections between the UE and HN; UE and SP; and UE and UE at various phases:  
* In phase 1, a primary authentication protocol is initiated when the UE presents a network access request. According to [6,10], a 5G-AKA or EAP-AKA' protocol can be selected as the AKA procedure between UE and HN.
* In phase 2, after primary authentication, the UE submits a service request that initiates a secondary authentication or authorisation process, which is handled by SMF in the HN network and SP AAA in the SP network. Depending on the registration status and security guidelines outlined in [11,12], the SAP-AKA or NS-FId protocols may be utilised at this time.
* In phase 3, UE sends a request for data caching and sharing authorisation after getting access to the services using the DCSS protocol described in [13].
* In phase 4, once the UE was given permission to cache and share data, it can publish that data by broadcasting the data name to other nearby UEs, in this example, \(UE_{A}\) and \(UE_{B}\). The DDSec and DDACap protocols are invoked by another UE after an interested UE sends it the request, as defined in [26].
# Engineering a Combinatorial Laplacian Solver: Lessons Learned +
## 1 Introduction  
Solving square linear systems \(Ax=b\), where \(A\in\mathbb{R}^{n\times n}\) and \(x,b\in\mathbb{R}^{n}\), is one of the most important problems in applied mathematics. It has widespread applications in science and engineering since it is at the heart of numerical simulations, which are in widespread use in academia and in industry, e.g., in tools like OpenFOAM [1]. In practice, system matrices are often sparse, i.e., they contain \(O(n)\) nonzeros. Ideally, the required time for solving sparse systems would grow linearly with the number of nonzeros \(2m\). Most direct solvers, however, show cubic running times and do not exploit sparsity. Furthermore, approximate solutions usually suffice due to the imprecision of floating point arithmetic. Exploiting this fact with sparse iterative solvers, such as conjugate gradient (CG), still yields a running time that is clearly superlinear in \(n\).  
[PERSON] and [PERSON] [2], following an approach proposed by [PERSON] [3], achieved a major breakthrough in this direction by devising a nearly-linear time algorithm for solving linear systemsin symmetric diagonally-dominant matrices. Nearly-linear means \(\mathcal{O}\big{(}m\cdot\mathrm{polylog}(n)\cdot\log(1/\epsilon)\big{)}\) here, where \(\mathrm{polylog}(n)\) is the set of real polynomials in \(\log(n)\) and \(\epsilon\) is the relative error \(\|x-x_{\mathrm{opt}}\|_{A}/\|x_{\mathrm{opt}}\|_{A}\) we want for the solution \(x\in\mathbb{R}^{n}\). Here, \(\|\cdot\|_{A}\) is the norm \(\|x\|_{A}:=\sqrt{x^{T}Ax}\) given by \(A\), and \(x_{\mathrm{opt}}:=A^{+}b\) is an exact solution (where \(A^{+}\) refers to the pseudoinverse of \(A\)). A matrix \(A=(a_{ij})_{ij\in[n]}\in\mathbb{R}^{n\times n}\) is diagonally dominant if \(|a_{ii}|\geq\sum_{j\
eq i}|a_{ij}|\) for all \(i\in[n]\).  
Symmetric matrices that are diagonally dominant (SDD matrices) have many applications, not only in applied mathematics, such as elliptic PDEs [4] and numerical simulations. They also play a major role in graph-based problems from (theoretical) computer science, such as, e.g., maximum flows [5], graph drawing [6] and graph sparsification [7]; also see [PERSON] and [PERSON] [8]. Thus, the problem inv-SDD of solving linear systems \(Ax=b\) for \(x\) on SDD matrices \(A\) is of significant importance. We focus here on Laplacian matrices (which are SDD) due to their rich applications in algorithms for undirected graphs, e.g., load balancing [9; 10] and image segmentation [11], but this is no major limitation [12].
## 4 Results of Oscillation Mode under Different Parameters
### Different Damping Coefficients
Related to the oscillation mode, the corresponding characteristics presented in each mode can be summarized as follows: (a) As the damping increases, the LL increases although the UL decreases as well as the self-excited region. Until the oscillation mode is transitioned from SG to CG, the LL and UL coincide, the self-excited region disappears, and the CV occurs. As the damping continues to increase, the CV continues to increase; (b) As the damping increases, the VIV branches gradually become complete, while the VIV-galloping branch and galloping branch gradually become incomplete. As the damping increases to a high value, the galloping branch disappears due to the limitation of velocity range. Therefore, the ability of the triangular prism to be excited (including self-excited and externally excited) from VIV to galloping is gradually weakened as the damping increases. Figure 11: Oscillation modes under different damping coefficients \(c\): (a) Amplitude ratio \(A^{*}\) versus reduced velocity \(U_{r}\); (b) Frequency ratio \(f^{*}\) versus reduced velocity \(U_{r}\).
## 2 Materials and Methods  
### Wdm  
WDM is an important feature in the expansion of optical communications. WDM has provided more flexibility to the system and simplified the network design. It helps with the enhancement of the system's capacity by sending multiple wavelengths over a single fibre [8]. A considerable increase in the data rate can be offered by WDM systems that are passed over a single fibre using multiple wavelengths, where a separate channel is carried at each wavelength. In WDM, the optical spectrum is divided into smaller channels; each can be used for transmitting and receiving data simultaneously [9].  
For the WDM system, each wavelength can be preserved as a discrete channel on which different data can be carried. A WDM multiplexer can be considered a passive device where light signals are combined with different wavelengths in a single fibre. The use of WDM for RoF signal distribution has gained importance in recent times. WDM enables the effective exploitation for the fibre bandwidth. The optical filter selection and wavelength stability limitations of semiconductor lasers, as well as the minimum channel spacing for commercial WDM, is approximately 50 GHz. This channel spacing can be reduced to 50 GHz or made equal to 25 GHz with a possibility of using hundreds of channels [10].  
The optical WDM network is illustrated in Figure 1, in which a substitution of the wavelength of frequency and a separated wavelength \(\lambda\)i are transmitted by each transmitter to different receivers [11]. WDM has the ability to transmit different frequencies without any interference in radio broadcasting [12]. Two types of WDM systems are dense wavelength division multiplexing and coarse wavelength division multiplexing.  
In the WDM technique, N optical wavelength numbers can be used as a data carrier, and these wavelengths can be combined with an optical fibre utilising WDM multiplexer, while at the receiver, the separation of these wavelengths as individual channels will be done by using a WDM demultiplexer. Each optical wavelength is different and typical; the gap between wavelengths controls the channel spacing to avoid the overlapping, which has happened in the optical carriers [13].  
Subcarrier Multiplexing (SCM) can be considered a complement of multiplexing techniques that can be utilised in optical systems for increasing the efficiency of bandwidth application. In an RoF system with SCM technique, multiple radio frequency RF signals multiplex in the frequency domain and are then transmitted at a single wavelength. SCM can be combined with WDM to provide a more flexible technique for optical transmission at high speed with high optical bandwidth efficiency in addition to high dispersion tolerance. This combination is more sensitive to noise effects; however, there is a disadvantage, as represented by the limitation of the maximum subcarrier frequencies and data rates.
# Dynamic Infection Spread Model Based Group Testing
## 1 Introduction
Motivated by the above points, in this paper, we consider dynamic testing algorithms over discrete time for a dynamic infection spread model with fixed, limited testing capacity at each time instance, where a full identification is not possible. In our system, test results are available immediately, and thus, the disease spread is not due to the delay between applying tests and receiving test results, but rather due to the limited testing capacity at each time instance. We follow a dynamic infection spread model, which is inspired by the well-known SIR model where the individuals are divided into three groups: susceptible individuals (S), non-isolated infections (I) and isolated infections (R), i.e., recovered individuals in classical SIR model. We do not assume a community structure in our system. We initialize our system by introducing the initial infections, and after that, at each time instance, infection is spread by infected non-isolated individuals to the susceptible individuals. Meanwhile, at each time instance, after the infection spread phase, the testing phase is performed, where a limited number of \(T\) tests are performed to detect a number of infections in the system. In our system, the objective is not to minimize the number of required tests to identify everyone at each time instance, but to control the infection spread either as soon as possible or with minimum number of people that got infected throughout the process, by using the given, limited, testing capacity \(T\) at each time instance. In this paper, we analyze the average-case performance of our system, i.e., the expected values of the number of susceptible individuals, non-isolated and isolated infections over time, which are random processes. For symmetric and converging algorithms, we state a general analytical result for the expected number of susceptible individuals in the system when the infection is brought under control, which is the time when there is no non-isolated infection left in the system. We present two dynamic algorithms: dynamic individual testing and dynamic Dorfman type group testing algorithm. We provide weak versions of these two algorithms and use our general result to obtain a lower bound on the expected number of susceptible individuals when the infection is under control. Finally, we run simulations to get numerical results of our proposed algorithms for different sets of parameters. The paper is organized as follows: in Section 2 we discuss the papers that are closely related to this paper, in Section 3 we present our system model, in Section 4 we present our proposed dynamic algorithms and our theoretical analysis, in Section 5 we present our simulation results, and finally in Section 6 we present the conclusions.
# Photodynamic Therapy--An Up-to-Date Review
## 6 Advantages and Disadvantages of Photodynamic Therapy  
Being so widely used, it is clear that PDT presents a series of advantages when compared to traditional therapy alternatives. One of the most important is spatiotemporal selectivity, which is owed to irradiation control in terms of position and time. This feature allows minimal invasiveness, minimization of systemic toxicity, and minimal functional disturbances [2,10].  
PDT is well-tolerated by the patients, can be repeatedly applied at the same site, and either no or only a slight trauma occurs when it is employed to treat target tissues inside the body [2,10]. Unlike other therapies, PDT also preserves fertility and does not affect pregnancy and delivery [9]. Moreover, ROS's ability to damage a broad range of cells makes PDT suitable for an extensive number of clinical and non-clinical applications [2].  
Even though PDT is a promising and beneficial treatment strategy for many diseases, its application is hindered by classic PSs. Their poor water solubility, limited light-penetration depth, and lack of good tumor targeting efficiency are the most commonly associated drawbacks to traditional PDT [8,14]. Other disadvantages include complex scheduling, the necessity of multiple procedures, patient observation after treatment, and photosensitivity issues during few weeks after therapy [13,33]. Therefore, developing a newer generation of PSs is a must in the advancement of PDT and its standardization in clinical practice.  
Another possibility of overcoming PDT limitations is represented by combinatorial approaches with other therapeutic modalities (Figure 5) [2]. In this way, the advantages of each treatment can be exploited, while their disadvantages can be offset. For instance, PDT might enhance antitumor immune response, and, in combination with immunotherapy, \"abscopal\" responses can be obtained from lesions too deep to be efficiently treated by PDT [11].  
Figure 5: Possible combinations between PDT and other therapeutic strategies. Created based on literature reference [11].
The tuning is based on signals recorded during static tests, which allows for the efficient synthesis of AHRS systems and other systems involving signal correction. These methods can be implemented for low-cost solutions without the need for sophisticated equipment. This approach will significantly improve measurement quality. Additionally, the statistical properties of the example results are discussed. This article is structured as follows: First, the principles of AHRS operation are described, along with the required accuracy. Next, the methodology for filter calibration is presented and the statistical properties of the signal received are discussed. Finally, a discussion is presented and future work is proposed.