Low Earth Orbit (LEO) Synthetic Aperture Radar (SAR) satellites conventionally rely on dedicated communication links, which impose prohibitive hardware, spectrum, and power overhead as satellite constellations scale. This paper presents CommSAR, a novel system that reuses existing SAR imaging waveforms to enable bidirectional communication without modifying satellite hardware or compromising imaging performance. For the downlink, data are embedded by modulating the starting frequency offset of the imaging waveform, preserving the waveform structure and imaging quality. For the uplink, we propose a compact, low-cost programmable metasurface to replace conventional large, expensive antennas, significantly lowering the barrier for dense ground station deployment. To handle extreme satellite dynamics, we employ an opposite-slope waveform as a pilot to compensate for mobility-induced effects. We implement a ground station prototype of CommSAR and validate its performance using an in-orbit commercial SAR satellite and a UAV SAR platform. Experimental results show that CommSAR preserves imaging performance without degradation while achieving downlink and uplink data rates of up to 105 kbps and 112 kbps, respectively, significantly outperforming the state of the art and demonstrating utility-grade performance.

The Hongtu-1 (HT-1) synthetic aperture radar (SAR) system is the first spaceborne single-pass multibaseline (MB) interferometric SAR (InSAR) system based on four HT-1 SAR satellites flying in a cartwheel formation. This setup includes three secondary satellites that function as receive-only units to create a compact multistatic SAR system. The primary objective of the HT-1 mission is to generate a consistent global digital elevation model (DEM) at 1:50000 scale. In addition, the HT-1 mission will feature novel SAR imaging technology demonstrations. On March 30, 2023, four HT-1 satellites were successfully launched and started to provide spaceborne radar data services to users. This article provides a detailed description of the HT-1 MB InSAR system, including the SAR performance, the cartwheel formation designed for multistatic SAR data collection with desired baselines, and the uninterrupted synchronization link. The interferometric performance is thoroughly analyzed. With the recorded data, imaging and interferometric processing procedures are introduced, and the capabilities of single-pass MB InSAR DEM generation are demonstrated. Compared with those of ICESAT, the height errors are less than 2 m in flat terrain and less than 5 m in mountainous terrain. Moreover, the resolution and swath of multisatellite mosaic imaging are 3 m and 80 km, respectively. The repeat-pass differential InSAR measurement for surface deformation monitoring is also included.

LuTan-1 (LT-1) is the first civil L-band synthetic aperture radar (SAR) satellite constellation and comprises two identical satellites. LT-1 is designed to fulfill two main requirements, one of which the main tasks is to provide digital surface model (DSM) products covering the areas that are not available using optical satellites. The second task is to provide deformation products to support the geohazard monitoring task. For the first task, LT-1 provides a novel noninterrupted imaging technology to facilitate phase synchronization. For the second task, the orbit maintenance is implemented using a newly proposed in-plane offset semimajor axis and out-of-plane control triggered strategy. Besides, we provide the system performance analysis for the two main tasks. Finally, the first results are produced with root-mean-square-error (RMSE) of the DSM less than 0.7 m in the flat region and 6.7 m in the mountainous region. The RMSE of the first deformation products is less than 2.7 mm in the test region. The results indicate a favorable potential for terrain mapping and deformation monitoring applications.

Over the past decade, jamming methods for Synthetic Aperture Radar (SAR) target detection and recognition, such as generating false targets, electromagnetic (EM) deception, and spoofing, have garnered significant attention. Distinguished from conventional SAR jamming methods, the target jamming scenario for SAR based on a new man-made material cloak introduces enhanced possibilities. These technologies exhibit the capability to effectively scatter incident EM waves in arbitrary or desired directions, thereby concealing pertinent information associated with the critical target. In this paper, we propose a broadband target jammer of SAR based on an information metasurface, which integrates intelligent information processing algorithms with space-time-coding digital metasurface, providing the capability to manipulate incident EM waves freely to achieve multi-mode jamming protections for critical targets. In simulation experiments, the results demonstrate adjustable EM deception and the generation of multiple false targets without any cooperation with the SAR system. Our work brings the available protection strategies for SAR closer to a wide range of real-time, broadband, and controllable applications, enhancing the concealment of critical targets in hot conflict zones.

The Hongtu-1 (HT-1) Synthetic Aperture Radar (SAR) constellation is the first in-orbit spaceborne single-pass multi-baseline interferometric SAR (InSAR) system. The system has the ability to conduct high-resolution earth observation and high-precision, high-efficiency terrain surveying. The highest resolution of the system is better than 0.5 m, and it has a 1:50000 scale global digital elevation model (DEM) and digital surface model (DSM) surveying capability. This paper provides a basic introduction to the HT-1 constellation, and demonstrates the advantages of single-pass multi-baseline InSAR results and its advantages over steep area.

With the growing scarcity of spectrum resources, frequency sharing among different systems is becoming quite common, which causes radio frequency interference (RFI) to normal SAR applications. Recently, in the RFI suppression field, algorithms based on the low-rank property (LRP) assumption have become a popular research topic. However, this assumption is not valid in complicated cases, especially when there is a wide variety of RFIs. To address this problem, in this paper, factors that affect the LRP are studied through theoretical analysis and simulation verification, a general RFI model is established to fit complicated cases, and an advanced RFI suppression scheme based on low-rank property restoration (LRPR) is proposed. The LRPR scheme has three steps. The first step is RFI localization, which captures the rough profile of the RFI in the time-frequency domain for RFI spectrum separation and extraction. The second step is RFI clustering, in which a novel similarity evaluation metric and corresponding two-step clustering algorithm are designed. The final step is RFI suppression. Operations for LRP recovery in each RFI group are proposed, consequently, classical low-rank approximation methods are applied for RFI suppression. The simulation results for various types of RFI show the robustness and performance improvement of the proposed scheme. In addition, in LuTan-1 data processing, the proposed scheme outperforms classical algorithms in both intensity image recovery and phase preservation.

The innovative bistatic synthetic aperture radar (BiSAR) mission LuTan-1 (LT-1) uses a noninterrupted synchronization scheme to achieve high-precision phase synchronization. While radio frequency interference (RFI) is a major factor in deteriorating phase synchronization performance. To present the effect of RFI on the synchronization phase clearly, the characteristics of RFI in the synchronization link are described in detail, and a precise analytic expression between the amplitude, frequency, and phase of RFI and synchronization phase error is established. Furthermore, a novel pulse-compression-based notch (PCN) method is proposed to eliminate the phase error introduced by RFI. In the proposed method, the saturated distortion signals resulting from strong interferences are detected and discarded by the distribution features of their modes. Then, inspired by contrary thinking, the synchronization signal after pulse compression is notched instead of RFI. A fast missing data iterative adaptive approach (Fast MIAA) is performed to recover the gaped RFI signal and remove it from the compressed signal. Finally, the correct synchronization phases can be extracted from the peak positions of the remaining signals. Experimental results derived from using simulated and real synchronization data of the LT-1 system validate the performance of the proposed RFI mitigation method.

Curvilinear spotlight SAR (CSSAR) has a high degree of freedom and can be used for 3-D imaging and video SAR (ViSAR) persistent imaging. The direct and effective processing of CSSAR data is an important part of CSSAR applications. However, CSSAR has higher requirements for motion compensation, especially when the motion measurement is not accurate enough. In this paper, an extended polar format algorithm (EPFA) is proposed based on the non-uniform fast Fourier transform for CSSAR. First, a theoretical derivation and analysis of the 2-D space-varying phase error in CSSAR are carried out. Then, a 2-D autofocus algorithm is proposed, which takes into account the spatial variability of the phase error. The efficiency of EPFA embedded in 2-D autofocus processing is significantly higher than that of back projection. In addition, based on the principle of small-angle approximation and spatial frequency domain sub-aperture technology, a novel ViSAR image generation scheme for CSSAR is proposed, which can significantly reduce the number of redundant calculations. The proposed algorithm is verified experimentally using data with a bandwidth of 2.4 GHz.

Efficient exploration remains a challenging problem in reinforcement learning, especially for tasks where extrinsic rewards from environments are sparse or even totally disregarded. Significant advances based on intrinsic motivation show promising results in simple environments but often get stuck in environments with multimodal and stochastic dynamics. In this work, we propose a variational dynamic model based on the conditional variational inference to model the multimodality and stochasticity. We consider the environmental state-action transition as a conditional generative process by generating the next-state prediction under the condition of the current state, action, and latent variable, which provides a better understanding of the dynamics and leads to a better performance in exploration. We derive an upper bound of the negative log likelihood of the environmental transition and use such an upper bound as the intrinsic reward for exploration, which allows the agent to learn skills by self-supervised exploration without observing extrinsic rewards. We evaluate the proposed method on several image-based simulation tasks and a real robotic manipulating task. Our method outperforms several state-of-the-art environment model-based exploration approaches.

Skyline query is a typical multiobjective query and optimization problem, which aims to find out the information that all users may be interested in a multidimensional data set. Multiobjective optimization has been applied in many scientific fields, including engineering, economy, and logistics. It is necessary to make the optimal decision when two or more conflicting objectives are weighed. For example, maximize the service area without changing the number of express points, and in the existing business district distribution, find out the area or target point set whose target attribute is most in line with the user’s interest. Group Skyline is a further extension of the traditional definition of Skyline. It considers not only a single point but a group of points composed of multiple points. These point groups should not be dominated by other point groups. For example, in the previous example of business district selection, a single target point in line with the user’s interest is not the focus of the research, but the overall optimality of all points in the whole target area is the final result that the user wants. This paper focuses on how to efficiently solve top‐k group Skyline query problem. Firstly, based on the characteristics that the low levels of Skyline dominate the high level points, a group Skyline ranking strategy and the corresponding SLGS algorithm on Skyline layer are proposed according to the number of Skyline layer and vertices in the layer. Secondly, a group Skyline ranking strategy based on vertex coverage is proposed, and corresponding VCGS algorithm and optimized algorithm VCGS+ are proposed. Finally, experiments verify the effectiveness of this method from two aspects: query response time and the quality of returned results.

Multi-scale methodology can enhance the performance of the model in deep learning. The current multi-scale methodology focuses on changing the formation, which will increase the parameters and calculations of the network. This paper offers a multi-scale method for data based on bit plane slicing(MBB). This expands the receptive field of valid information in image data. It is done by multi-level fusing image with high bit planes. Our experimentation shows that by adding MBB in front of the backbone network, one can achieve a significant performance improvement. The MBB approach is widely applicable because it does not require changes to the structure of the backbone network.

The bistatic synthetic aperture radar (BiSAR) plays an important role in remote sensing. However, the deviation between the two oscillators in BiSAR systems will cause a residual modulation of the echo signal. Therefore, the phase synchronization is an important issue that must be addressed in the BiSAR system. An advanced noninterrupted phase synchronization scheme is used for LuTan-1. The synchronization pulses are exchanged immediately after the ending time of the radar echo receiving window and before the starting time of the next pulse repetition interval, which will not interrupt the normal SAR operation. In order to evaluate the accuracy of the phase synchronization scheme, the model of phase synchronization is introduced at first. The hardware design and processing flow of LuTan-1 are introduced in detail. An innovative internal calibration strategy is also described. Then, the test data acquired by the ground validation system are analyzed to verify the effectiveness of the phase synchronization scheme. The signal-to-noise ratio (SNR) and the synchronization rate are the two most important factors to influence the accuracy in phase synchronization. The conclusions have guiding significance for the synchronization module design of LuTan-1 and the future BiSAR system.

The Internet of Things (IoT) is creating billions of connected devices and generating enormous amounts of data. Data needs to be stored efficiently so that it can be retrieved easily on demand. Cloud storage is an inevitable choice for data management for IoT. Because of application diversity, limited bandwidth of end devices and the demand for real time, it is necessary to decrease the cost of data access in Heterogeneous Distributed Cloud Storage System (HDCSS). According to the point that applications always access the partial data, this paper combining the data access rate, proposes a degraded read scheme based Local Reconstruction Code (LRC) to improve the local max throughput in HDCSS. Simulation results show that our proposed scheme can achieve about a 50% increase in local throughput of hot data blocks without adding additional access load compared with commonly used LRC.

Phase synchronization is one of the key issues that must be addressed for the bistatic synthetic aperture radar (BiSAR) system. LuTan-1 (LT-1) is an innovative spaceborne BiSAR mission based on the use of two radar satellites operating in the L-band to generate the global digital terrain models in the bistatic interferometry mode. An advanced synchronization scheme is used for the LT-1 system. The synchronization pulses are exchanged immediately after the ending time of the radar echo-receiving window and before the starting time of the next pulse-repetition interval. Therefore, it cannot interrupt the normal SAR data acquisition, further improving the synchronization accuracy and avoiding the data missing effect. In this letter, a robust phase-error estimation and compensation method is proposed to improve the accuracy of the synchronization by using the Kalman filter. The test data acquired from the ground validation system of the LT-1 synchronization module are used to demonstrate the feasibility of the proposed scheme. The results validate the effectiveness of the proposed scheme and prove the promise for its future application in LT-1.

LuTan-1 (LT-1), i.e., TwinSAR-L, mission is an innovative spaceborne bistatic synthetic aperture radar (SAR) mission that is based on two satellites operating at L-band with flexible formation flying, which is planned to launch in 2020. The primary objective of LT-1 is to generate a highly accurate global digital elevation model (DEM). Beyond that, LT-1 will serve for the demonstration of some state-of-the-art technologies in radar field and some applications, such as biomass inversion, disaster forecasting, and climate and environmental monitoring, and phase synchronization is a technical challenge in realizing the highly accurate topography and deformation measurements. The pulsed alternate synchronization scheme, which is proposed to solve the synchronization problem of TerraSAR-X add-on for Digital Elevation Measurements (TanDEM)-X, is an efficient and accurate method. However, it interrupts the normal work of the TanDEM-X, accordingly flowing a series of problems. For LT-1, a novel synchronization scheme, in which the phase synchronization signal is exchanged by virtue of a time slot between radar signals, is applied. Thus, the working efficiency and synchronization accuracy can further be improved. Furthermore, the performance prediction and phase synchronization experiment for this synchronization scheme is presented, which verifies the feasibility of the proposed scheme. Finally, in order to guarantee the transmission quality of the synchronization signal, the illumination combinations and gain variation of the synchronization antenna in an orbital period are detailed.

LuTan-1 [(LT-1), i.e., TwinSAR-L] mission is an innovative spaceborne bistatic synthetic-aperture radar (BiSAR) mission focusing mainly on differential interferometry, which will be launched in 2020. This article introduces some important aspects of the LT-1 mission for the first time, including the formation configuration, imaging mode, application scenarios, and the efficient baselines between the master satellite and the slave satellite. To realize the high accurate topography and deformation measurements, a wide swath BiSAR focusing algorithm with phase reserving ability should be developed. This article proposes a modified bistatic range-Doppler algorithm based on 2-D principle of stationary phase spectrum, which reduces the phase error introduced by the root term expansion and has an excellent focus performance and a good phase reserving ability. Finally, the spaceborne bistatic simulation experiments using orbital parameters and imaging mode of the LT-1 mission, including point targets and scene targets, are utilized to illustrate the validity and accuracy of the proposed algorithm.

LuTan-1 (LT-1) refers to an innovative mission of spaceborne bistatic synthetic aperture radar (BiSAR) adopting the phase synchronization scheme of pulse exchange, which is scheduled to be launched in 2020. In this mission, the multipath effect caused by the reflection of satellites and Doppler frequency shift resulting from the relative motion between satellites constitute two critically latent factors deteriorating the performance of the phase synchronization scheme. This article details a loss factor to evaluate the fading of synchronization signals under the reflection of smooth and rough surfaces and estimates the influence of Doppler frequency shift on synchronization signals. Furthermore, the multipath channel impulse response is modeled, and the correlation characteristics of multipath channel are described by the coherent bandwidth and coherent time. In addition, two simulation experiments based on the system parameters of LT-1, are implemented to assess the influence of time-invariant and -varying multipath effects on the phase synchronization scheme. A scale experiment is also executed to quantify the influence of multipath effect on phase synchronization, and its result demonstrates that the phase synchronization scheme of LT-1 can not only achieve full coverage of space and backup capability of pulse exchange but also meet the application requirements under multipath effect.

Digital beamforming (DBF) with Scan-On-Receive (SCORE) in elevation is a powerful technique for spaceborne synthetic aperture radar (SAR) to achieve high-resolution wide-swath (HRWS) images. DBF in spaceborne SAR should be implemented in real-time to reduce the volume of the downloaded data. Current digital beamformers in SAR systems usually use phase shift instead of a time delay network to ensure real-time implementation. However, conventional phase shift DBF SAR with narrow array bandwidth is not applicable for broadband signals. The beam steering deviation as a function of frequency is obvious for signals with large fractional bandwidth, which appears as a phenomenon of frequency dispersion. If the signal bandwidth is wider than the array bandwidth, frequency dispersion can significantly deteriorate the signal-to-noise ratio (SNR) and must be well relieved. This article analyzes the frequency dispersion in DBF SAR and proposes an innovative DBF-SCORE scheme with specially designed scalloped beam. The proposed digital scalloped beamforming (DSBF) scheme is effective in relieving the influence of frequency dispersion in DBF SAR. Theoretical analysis and simulation results validate the effectiveness of the proposed scheme. The proposed DSBF scheme gives practical solution to the problem of frequency dispersion in broadband DBF SAR, which makes DBF-SCORE a more practical technique for future spaceborne HRWS SAR.

Network selection is one of the important techniques in cognitive radio networks (CRNs). With the development of network convergence technology and the popularity of heterogeneous networks, multiple primary CRNs interacting with multiple authorized networks are becoming possible, which can provide secondary users with more spectrum resources by network selection. Network selection is the key to spectrum sharing between CRNs and multiple primary networks. However, the spectrum sensing results, highly complex system state, and unsystematic research framework make the research of network selection very challenging. Traditional network selection algorithms are offline selection methods that are based on prior knowledge of primary networks. However, in the complex network environment, it is impossible to get prior knowledge from multiple primary networks, because the offline network selection methods lack efficiency. In order to meet these challenges, this article aims at improving the quality of service of cognitive users, and based on reinforcement learning method and the achievements of dynamic spectrum access of cognitive radio in single primary network environment, proposed a deep reinforcement learning based online network selection method of CRNs with multiple primary networks.

The phase synchronization is one of the key issues to be addressed for the bistatic synthetic aperture radar system. In this paper, an advanced non-interrupted phase synchronization scheme is proposed. Both satellites are equipped with four synchronization antennas for a mutual exchange of synchronization pulses, which are transmitted rightly after the radar signal transmitting and before the echo receiving. Therefore, it can not interrupt the normal SAR data acquisition, which can further improve synchronization accuracy and avoid the data missing effect. The ground validation system for TwinSAR-L synchronization module is described in detail. The results are also evaluated to demonstrate feasibility of the proposed scheme.

Generally, synthetic aperture radar (SAR) system transmits linear frequency modulation (LFM) signal to obtain the high-resolution image and weighted windowing is usually employed to suppress sidelobes. However, it will cause a 1-2-dB signal-to-noise ratio (SNR) loss. Nonlinear frequency modulation (NLFM) signal, which can construct the signal's power spectral density (PSD) to reduce sidelobes without loss of SNR, is a promising candidate. However, the real-time generation of precise NLFM signal is still a technical challenge. In this letter, a high-precision NLFM signal generator with the ability of predistortion compensation is developed, and this signal generator will be employed in LuTan-1 (LT-1, i.e., TwinSAR-L) mission which is an innovative spaceborne bistatic SAR mission and planned to launch in 2020. In addition, a two-step error compensation method is developed to compensate the system error. Finally, the ground experiment is performed to validate the designed signal generator.

Enterprise Digital Rights Management (EDRM) was developed to help corporations keep digital documents secure, as one of many digital information security solutions. However, these security mechanisms typically reduce the work efficiency of the staff by making them spend time working on non-project related tasks. It is therefore of business importance to determine the total amount of loss in efficiency and productivity and the factors that impact this reduction in productivity. In this study, the loss of efficiency was quantified using the concept of non-productive time (NPT). The total amount of NPT associated with EDRM is related to the business process and human behavior of the employees, for example, the documentation classification system, average response time from system administrators, and percentage of failures in opening authorized documents. Parameters that define the business model of the corporation quantitatively and have an impact on NPT are identified and potential data collection techniques for these parameters are also proposed. A Petri-net model is built to simulate the business process of implementing an EDRM product. The sensitivity of NPT associated with the EDRM product to these parameters was evaluated using this Petri-net model. The parameters are ranked according to their relative importance. This study has the potential to help information security managers to make informed security investment decisions and to take actions toward reducing the impact of EDRM, so that a balance is kept between information security expense, resource drain and effectiveness of security products.