esa-sceva/satcom-chunk-collection huggingface dataset:
# Modeling and Control of Satellite Formations: A Survey
###### Abstract  
This survey deals with the problem of the group motion of spacecraft, which is rapidly developing and relevant for many applications, in terms of developing the onboard control algorithms to ensure the fulfillment of a given mission. The paper provides a comprehensive overview of spacecraft formation flight control. The bibliography is divided into three main sections: the multiple-input-multiple-output approach, in which the formation is treated as a single entity with multiple inputs and multiple outputs; the leader-follower formation, in which individual spacecraft controllers are linked hierarchically; and a virtual structure formation, in which spacecraft are treated as rigid bodies embedded in a common virtual rigid body. This survey expands a 2004 survey and updates it with recent results.  
satellite formation; autonomous; circumnavigation; guidance; control; Hill-Clohessy-Wiltshire; orbit; leader-follower; multiple-input-multiple-output; consensus; sliding mode +
Footnote †: journal: Information and Control Systems  
1
Footnote 1: [[https://doi.org/10.3390/automation3030026](https://doi.org/10.3390/automation3030026)]([https://doi.org/10.3390/automation3030026](https://doi.org/10.3390/automation3030026))  
2022 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)]([https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)) 4.0/).
## 3 Results and Discussion
### Spatial Distribution  
The spatial distribution of the ice along the rotor radius is briefly presented. The spatial distribution is achieved with the deployment of a three-nozzle setup. Each nozzle sprays in a specific range of the rotor radius. In Figure 6, the averaged profile line (rotor baseline) can be found. Because the line is evaluated with regards to a reference line, negative values at the left side near the clamping (radius 60-120 mm) are caused by the fact that the rotor has an uneven surface. The clamping covers an area with a radius of approximately 50 mm and is, therefore, not considered in the graph. Due to the elevated position of the clamping, it creates a flow barrier at close range and, thus, increases unintended ice accumulation at the edge. This area is, therefore, hatched in the figure.  
The changes in the modal properties, caused by different icing conditions, show a strong dependence on the ice distribution as well as on the ice thickness. Specifically, decreasing natural frequencies can be observed for all mode shapes as the ice accumulates at the rotor surface with the nozzle setup (1, 1, 1). In Table 3, the frequency deviation for the three spate nozzle configurations can be found, and they are also depicted in Figure 7. Since the temperature equilibrium varied between measurements depending on the ambient conditions, the natural frequencies in the initial state also differed from those in Table 2, and are, therefore, not specifically listed here. Due to the fluctuations in the actual ice thickness, the shifts of the natural frequency are listed together with the corresponding maximum thickness value.  
Figure 6: Thickness profile of ice accumulation along the radius of the rotor at constant rotational speed using three different nozzle configurations to form ice on the inner radius (**a**), in the centre (**b**) and on the outer radius of the rotor (**c**).  
An ice increase at the outer rotor radius, Figure 6 (left), causes decreasing eigenfrequencies for the first four eigenmodes, due to the maximum deflection of the corresponding mode shapes and the mass increase in the same area. Mode shapes containing nodal lines in the middle perimeter of the rotor do not exhibit any drastic frequency shifts.
## 4 Loss Reduction Optimization Design
### Thermal Performance Improvement Assessment  
The thermal performance improvement assessment of the optimized high-speed magnetic field-modulated motor reveals significant enhancements in heat dissipation capabilities and temperature distribution characteristics across all critical components. Comprehensive thermal analysis demonstrates that the implementation of advanced cooling strategies and optimized electromagnetic design resulted in a 45.3% reduction in maximum temperature rise under identical operating conditions. The temperature distribution exhibits substantially improved uniformity, with maximum temperature gradients decreasing from 38.7 \({}^{\circ}\)C to 16.2 \({}^{\circ}\)C across active components, effectively mitigating the risk of thermal stress-induced demagnetization and material degradation. Transient thermal response testing verifies enhanced thermal stability during rapid charging and discharging cycles, with temperature rise rates decreasing by 52.7% compared to the original design. Three-dimensional thermal mapping reveals that the innovative dual-material permanent magnet configuration dramatically reduced hotspot formation at the magnet-modulator interface, maintaining temperatures below the critical threshold throughout the entire operating envelope. The strategic implementation of integrated micro-channel cooling structures within the modulator assembly demonstrates exceptional effectiveness, reducing thermal resistance by 63.8% while minimizing the impact on electromagnetic performance.  
As illustrated in Figure 11a, axial Temperature Distribution shows the significant reduction in peak temperatures from 140 \({}^{\circ}\)C to 95 \({}^{\circ}\)C along the motor's axial length, with substantially reduced temperature gradients. The shaded regions represent measurement uncertainty bounds, demonstrating improved stability in the optimized design. As shown in Figure 11b, dynamic thermal impedance measurements confirm the reduction in thermal time constants from 387 s to 142 s, enabling significantly faster thermal stabilization following load transients. Infrared thermography conducted during extended operation verifies the computational predictions, with measured temperature distributions closely matching simulated profiles within a 5.3% margin. The enhanced thermal performance directly contributed to efficiency improvements by maintaining optimal material properties across diverse operating conditions, particularly evident during high-speed operation where the temperature-dependent performance degradation was substantially mitigated. This comprehensive thermal improvement enables reliable extended operation of the flywheel energy storage system across the full operational spectrum, effectively addressing one of the critical limitations of high-speed magnetic field modulated motors in energy storage applications.  
Figure 10: Three-dimensional loss distribution comparison.
# Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors
## 2 Materials and Methods  
### Site Description  
Our study site is an unmanaged, mixed-temperate secondary forest located at the Pace Estate (37.9229, -78.2739), a property in holding of the University of Virginia, near Palmyra, Virginia, approximately 20 miles east of Charlottesville. The forest has an average stem density of 1813 trees ha\({}^{-1}\), and is populated by _Acer rubrum_, _Quercus alba_, _Fagus grandifolia_, _Pinus virginiana_, and _Nyssa sylvatica_ of similar composition to other mesic, temperate mid-Atlantic secondary growth forests, and has no recorded history of management during the past century. Precipitation averages 1240 mm y\({}^{-1}\) with a mean annual temperature of 13.9 \({}^{\circ}\)C [27; 28].
# Efficient Mobile Vehicle Data Sharing Scheme Based on Consortium Blockchain
## 5 Simulation Analysis
### Performance Analysis of the Stackelberg Game Solution Scheme
#### 5.1.2 Simulation Analysis
Overall, the BCB scheme is higher for the buyers, but the revenue of the SPRS scheme at 100 exceeds the BCB scheme. The reason is that in the SPRS scheme, the response time of vehicles is a random value. When the number of vehicles becomes 100, the overall response time of vehicles in the network becomes long. In this case, the overall bid of the buyer is low, the total cost of buying the same data is lower, and the buyer indirectly improves the benefit, which is the reason for the higher income of the buyer in the SPRS scheme. However, this is a special case, in which the number of vehicles and shared data continue to increase; after repeated simulation and calculating the average value, the probability of this special case is greatly reduced. In summary, the BCB scheme has significant advantages in terms of overall performance. The following will study the relationship between the buyer's inconvenience sharing parameters \(\alpha\) and the buyer benefit and cost in the BCB scheme. Assuming consistent \(\alpha\) values for the whole vehicle, fluctuating in the range of [0.04, 0.32], the presence of 50 random vehicles on the 600 m \(\times\) 600 m network area roads, offer \(p_{arg}=0.5 RC\), \(\eta_{i}=1 RC/GB\), balance parameters, \(\beta_{i}=1\), the maximum data that all vehicles are willing to provide is \(D_{k}\) consistent and equal to 2 GB. To ensure that the data meet the general requirements, 50 simulations are completed, with the average as the final result, drawing the buyer income fluctuation map in the POS scheme with the same amount of purchase data. The simulation results are detailed in Figure 6.  
3. Impact of the inconvenience parameters \(\alpha\) on the buyer's benefit and cost  
Figure 6 shows that during the \(\alpha\) continuous improvement of the BCB parameters, the buyer's income in the BCB scheme continues to decrease, while the cost shows the opposite trend. The root cause is that when the seller is under the influence of various factors, the buyer will increase the bid and enhance the seller's tendency to share, so that the buyer needs to bear higher costs, and the benefits will be affected. In addition, in the POS scheme, the \(\alpha\) income is also negatively correlated, because we assume the same data purchase volume under the two sets in the simulation analysis. In the \(\alpha\) of raising the case, the data purchase volume in BCB and POS scheme decreases, and the buyer benefit and data purchase volume of the POS scheme are positively correlated, so the income in the buyer's scheme is also reduced.
## 2 Regulatory Framework and Guidelines
### Soil Protection and Brownfield Rehabilitation  
Brownfields are defined as polluted and abandoned sites where urban transformation interventions combine remediation and reuse [27; 28]. At international level, soil protection, reducing land degradation and consumption, and strategies for representing city spaces are among the 2030 Agenda Goals for Sustainable Development [14; 29].  
The EU targets to achieve zero net land take by 2050 [30]. In fact, soil is fundamental for life on Earth and is a non-renewable resource [31]. Spatial planning strategies for urban expansion cause most of soil sealing. The EU Commission emphasized the need to implement good practices to reduce the negative effects of soil consumption and, in particular, to reduce soil sealing [32; 33], identified as major threats to the environment [31].  
Given the condition of fragility and criticality of the territory, soil protection, the sustainable management of natural resources, and arrested land consumption and desertification are crucial for the Italian context [34]. The Italian brownfield regulation falls under waste regulations, in which brownfield redevelopment is divided into site environmental remediation and subsequent urban redevelopment [35]. At the regional level, Lombardy Regional Law 16/2017 defined a digital catalogue of brownfields and introduced the con cept of 'ecological soil balance' and economic incentives for brownfield renovations and limitations on green fields use for new construction projects [36; 37]. In addition, at project level, CAM introduced the need and indications to reduce land use and sealing, prioritizing the recovery of existing abandoned buildings and brownfields [26].  
Concerning brownfield renovations, the presented research aims to:  
* test the proposed methodology on a brownfield renovation;
* evaluate the advantages of proper waste audit definition and CDW management for the extensive demolition phase planning of an abandoned industrial area.
## 3 Results  
In our experiment, the multiple vital signs concurrent detection was carried out to several people simultaneously using one radar device. The radar device was mounted at a certain distance from people whose vital signs were being measured. The radar transmitted millimeter waves to several people at once, and then the radar captured the waves reflected from each person.  
The reflected waves captured by the radar were then processed in signal processing as described in Section 2 to produce the heartbeat rate and breathing rate of several people at once. The radar then showed each person's heartbeat rate, breathing rate, heartbeat waveforms, breathing waveform, chest displacement waveforms, and range angle graph on a computer monitor screen.  
The results of the vital signs measurement are shown in Figures 8-12. There are several quantities demonstrated in these pictures. First is the Range Angle Map. Next is the Chest Displacement chart. Then the Breathing Waveform graph is also shown. Next, the Heart Waveform graph is displayed. All of the graphs show the results of the multiple concurrent vital sign measurements for four targeted people.  
Figure 7: Computer programming flow.  
Figure 8: Data 1.  
Figure 10: Data 3.  
Figure 9: Data 2.  
Besides that, the breathing rates and heartbeat rates of the four people being targeted are also shown in the form of numbers simultaneously, so that the users can directly read it. In that display of numbers, these measurement results of rates are referred to as vitalSigns_1, vitalSigns_2, vitalSigns_3, and vitalSigns_4.  
The results of the vital signs measurement by the oximeter as a comparison are shown in Figure 13a-d and written in Table 2 as follows:  
Figure 11: Data 4.  
Figure 12: Data 5.
## 4 Results and Discussion
### A Thermodynamic Approach to Data Processing
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Predict** & & & & **Training** & & & & & & **Test** & \\ \hline \multirow{4}{*}{**Target**} & Very dissatisfied & 4 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 \\  & Dissatisfied & 0 & 4 & 1 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 \\  & Slightly dissatisfied & 0 & 1 & 7 & 1 & 0 & 0 & 0 & 3 & 1 & 0 & 0 \\  & Slightly satisfied & 0 & 0 & 1 & 17 & 2 & 0 & 0 & 0 & 1 & 7 & 1 & 0 \\  & Satisfied & 0 & 0 & 0 & 7 & 75 & 8 & 0 & 0 & 0 & 4 & 36 & 5 \\  & Very satisfied & 0 & 0 & 0 & 0 & 14 & 133 & 0 & 0 & 0 & 0 & 7 & 68 \\ \hline \multirow{4}{*}{**Target**} & Very dissatisfied & 7 & 1 & 0 & 0 & 0 & 0 & 3 & 0 & 0 & 0 & 0 \\  & Dissatisfied & 0 & 6 & 1 & 0 & 0 & 0 & 0 & 3 & 1 & 0 & 0 & 0 \\  & Slightly dissatisfied & 0 & 1 & 11 & 2 & 0 & 0 & 0 & 0 & 7 & 1 & 0 & 0 \\  & Slightly satisfied & 0 & 0 & 4 & 77 & 3 & 0 & 0 & 0 & 3 & 36 & 3 & 0 \\  & Satisfied & 0 & 0 & 0 & 9 & 105 & 7 & 0 & 0 & 0 & 4 & 52 & 4 \\  & Very satisfied & 0 & 0 & 0 & 0 & 3 & 38 & 0 & 0 & 0 & 0 & 2 & 18 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Confusion matrix of the ANN model for predicting customers’ overall opinions on the lab’s services in both scenarios. The accuracy of the ANN model in the BCS is 87.3% (240 out of 275 instances correctly identified) and 86.1% (118 out of 137 instances correctly identified) for the training and test sets, respectively. In the WCS, these metrics are 88.7% (244 out of 275 instances correctly identified) and 86.9% (119 out of 137 instances correctly identified) for the training and test sets, respectively. Thus, the ANN model demonstrates good effectiveness in predicting customers' overall opinions regarding the lab's service, attaining accuracy levels close to 90%. This model provides insights into customer satisfaction, identifies areas for service improvement, and helps prioritize actions based on simulated scenarios. By predicting multiple scenarios, the model offers several advantages for the water lab, including proactive management through forecasting various potential conditions and challenges and enhancing the customer experience by anticipating needs and addressing concerns more effectively. Developed based on historical data, including customer feedback and performance metrics, the model predicts how changes in factors such as service quality or response times impact customer satisfaction. It identifies key variables with the most significant impact, highlights performance gaps, and helps prioritize actions based on their potential effects. Additionally, the model forecasts potential challenges and guides resource allocation, ensuring proactive management. With continuous updates and refinement, the ANN model supports ongoing improvement by adapting to evolving customer needs and preferences.
# Analysis of the Dihedral Corner Reflector's RCS Features in Multi-Resource SAR
## 4 The RCS Features of the CR Array in Multi-Resource SAR
### The Theoretical Deformation Monitoring Accuracy in the Theory of the CR Array  
SCR is the key to estimating the theoretical deformation monitoring accuracy [19,28], which is commonly used in PSInSAR time-series analyses to assess the deformation monitoring capabilities achievable for permanent scatterers. The deformation monitoring accuracy is calculated using the following equation:  
\[d_{e}\approx\frac{\lambda}{4\pi}\times\frac{1}{\sqrt{\text{SCR}}} \tag{7}\]  
In engineering applications, achieving a deformation monitoring accuracy of 1 mm necessitates the design of appropriate panel dimensions and tilt angles. This can be accomplished by considering both the background energy and the RCS values of CRs. Figure 11 illustrates the theoretical deformation monitoring accuracy of CRs corresponding to the SCR value under the Sentinel and TSX data in this study.  
In the Sentinel data (refer to Figure 11a), the theoretical deformation monitoring accuracy by the measured SCR corresponding to the dihedral CR with a semicircular panel with a diameter of 0.6 m fluctuates within the range of 1 to 1.5 mm. The dihedral CR square panel with a side length of 0.4 m has a slightly larger effective reflective area compared to the dihedral CR with semicircular panels with a diameter of 0.6 m. An increase of the deviation angle to 12\({}^{\circ}\) leads to a maximum reduction in accuracy by nearly 0.5 mm, highlighting the significant impact of the deviation angle on monitoring precision, particularly in CRs with smaller panel sizes. The dihedral or triangular CRs with larger panel sizes, such as those 0.8 m in diameter, meet the demands for millimeter-level deformation monitoring across different deviation angles.  
In the TSX data (refer to Figure 11b), the measured SCR for the smallest-sized dihedral CR with semicircular panels with a diameter of 0.6 m is around 25 dB, corresponding to a theoretical deformation monitoring accuracy of 0.14 mm. The accuracy of all corner reflectors is within 0.2 mm, with negligible influence on the deviation angle change. The statistical analysis of deformation monitoring accuracy across various types of CRs indicates that on a slope, the dimensions of the CR can be further reduced for TSX data for millimeter deformation accuracy. According to the proposed RCS model (Equation (4)) and SCR formula (Equation (7)), and considering the background scatter intensity of the Huangtupo slope, an SCR of 10 dB is enough to reach millimeter deformation level, which means a dihedral CR with square panel with a side length of 0.2 m or semicircular panel with a diameter of 0.3 m for dihedral CRs can achieve deformation monitoring accuracy at the 1 mm level.
## Abbreviations  
AWGN: additive white Gaussian noise; BER: bit error rate; FET: field-effect transistor; FOV: field of view; ITS: intelligent transportation system; LED: light-emitting diode; NRZ: Non-Return-to-Zero; OOK: on-off keying; PHY: physical layer; PPM: Pulse Position Modulation; RF: radio frequency; Rx: receiver; SNR: signal-to-noise ratio; Tx: transmitter; V2V: vehicle-to-vehicle; VLC: visible light communication
# Sparse Envelope Spectra for Feature Extraction of Bearing Faults Based on NMF
## 3 Results
### Experimental Verification
#### 3.2.1 Case 1
Figure 12: Spare envelope spectra are obtained with decomposed sub-matrices: (**a**) Basis \(\mathbf{w}_{3}\) and weight vector \(\mathbf{h}_{3}\); (**b**) Basis \(\mathbf{w}_{4}\) and weight vector \(\mathbf{h}_{4}\); (**c**) Basis \(\mathbf{w}_{5}\) and weight vector \(\mathbf{h}_{5}\). \(f_{\rm i}\) = fault characteristic frequency. To compare the effects, band-pass filtering is also applied. Figure 14 shows the envelope demodulation results with the three frequency bands. Because of the large in-band noise, the fault characteristic frequency is influenced by other frequency components. Compared with the result of Figure 12, due to the combination of the time domain envelope of the impulse response shown in Figure 15, the proposed method can obtain the sparse envelope spectrum constructed with the frequency basis \(\mathbf{w_{3}}\) and the weight \(\mathbf{h_{3}}\), thereby effectively extracting the fault characteristic frequency. Figure 14: Envelope spectrum with band-pass filtering: (**a**) Filtered with \(\mathbf{w}_{3}\); (**b**) Filtered with \(\mathbf{w}_{4}\); (**c**) Filtered with \(\mathbf{w}_{5}\). Figure 9:0 Position of three frequency band filtering. Additionally, the fast spectral kurtosis method is also used to analyze the signal. The results are shown in Figure 9:1 The optimal demodulation band is located in the 2625-3125 Hz region, and the waveform and spectrum of the filtered signal are presented in Figure 16b,c. Compared with the proposed method, although the envelope spectrum obtained by the fast spectral kurtosis method contains fault characteristic frequencies, it also contains many interference components, which increases the difficulty of identification and is not as simple and intuitive as the sparse spectrum.