Space-Time Cascaded Processing-Based Adaptive Transient Interference Mitigation for Compact HFSWR
Remote Sensing, 2023 In high-frequency (HF) radar systems, transient interference is a common phenomenon that dramatically degrades the performance of target detection and remote sensing.
Di Yao, Qiushi Chen, Qiyan Tian
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Space-Time Adaptive Processing by Employing Structure-Aware Two-Level Block Sparsity
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Traditional radar space-time adaptive processing (STAP) cannot efficiently suppress heterogeneous clutter because of a small number of independent and identically distributed training snapshots.
Zhizhuo Jiang +4 more
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Deep learning for high‐resolution estimation of clutter angle‐Doppler spectrum in STAP
IET Radar, Sonar & Navigation, 2022 Space‐time adaptive processing (STAP) methods can provide good clutter suppression potential in airborne radar systems. However, the performance of these methods is limited by the training samples' support in practical applications. To address this issue,
Keqing Duan +3 more
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ADMM-Based Low-Complexity Off-Grid Space-Time Adaptive Processing Methods
IEEE Access, 2020 In this paper, we consider the problems of off-grid effects elimination and fast implementations for sparse recovery based space-time adaptive processing (SR-STAP) methods.
Zhongyue Li, Tong Wang
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An Efficient Sparse Bayesian Learning STAP Algorithm with Adaptive Laplace Prior
Remote Sensing, 2022 Space-time adaptive processing (STAP) encounters severe performance degradation with insufficient training samples in inhomogeneous environments. Sparse Bayesian learning (SBL) algorithms have attracted extensive attention because of their robust and ...
Weichen Cui +3 more
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Robust Space-Time Adaptive Processing Method for GNSS Receivers in Coherent Signal Environments
Remote Sensing, 2023 In the coherent signal environments caused by multipath propagation, the interference suppression performance of the global navigation satellite systems (GNSS) receivers decreases sharply.
Zhen Meng, Feng Shen
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Training sample selection for space–time adaptive processing based on multi-frames
The Journal of Engineering, 2019 As training samples are not identically distributed with cell under test (CUT) in heterogeneous environments, the performance of space–time adaptive processing (STAP) to suppress clutter degrades. To improve the performance of STAP, this study proposes a
Chenxiao Zhang +3 more
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Robust Constrained Inverse Beamforming Algorithm Based on Space Time Adaptive Processing
IEEE Access, 2019 The power of Beidou satellite signals is very low, so it is vulnerable to interfering sources and in the presence of jamming. Therefore, a robust constrained inverse beamforming algorithm based on space-time adaptive processing is proposed, which can not
Yanping Liao +3 more
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A Space-Time Adaptive Processing Method Based on Sparse Reconstruction of Reverberation Interference
Xibei Gongye Daxue Xuebao, 2020 Aiming at the problem of how to obtain reverberation samples and estimate their covariance matrix in the space-time adaptive processing(STAP) of sonar system, a new space-time adaptive processing method is proposed based on sparse reconstruction of ...
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Coprime arrays and samplers for space-time adaptive processing [PDF]
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015 This paper extends the use of coprime arrays and samplers for the case of moving sources. Space-time adaptive processing (STAP) plays an important role in estimating direction-of-arrivals (DOAs) and radial velocities of emitting sources. However, the detection performance is fundamentally limited by the array geometry and the temporal samplers at each ...
Chun-Lin Liu, Palghat P. Vaidyanathan
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