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Space-Time Adaptive Processing (STAP) for Low Sample Support Applications
, 2004 H. Schuman, Ping Li
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IEEE Transactions on Aerospace and Electronic Systems, 2023
Sparse recovery space-time adaptive processing (SR-STAP) can achieve an ideal clutter suppression with very few training samples, however, its application faces two challenges: 1) severe gird mismatch effect and 2) large time-resources requirement.
N. Cui, Kun Xing, Zhongjun Yu, K. Duan
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Sparse recovery space-time adaptive processing (SR-STAP) can achieve an ideal clutter suppression with very few training samples, however, its application faces two challenges: 1) severe gird mismatch effect and 2) large time-resources requirement.
N. Cui, Kun Xing, Zhongjun Yu, K. Duan
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IEEE Transactions on Geoscience and Remote Sensing, 2022
When an early warning radar installed in a spaceborne platform works in a down-looking mode to detect a low-altitude flying target, the severely broadened main-lobe clutter cannot be ignored, which will cause the deterioration of the moving target ...
Penghui Huang +4 more
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When an early warning radar installed in a spaceborne platform works in a down-looking mode to detect a low-altitude flying target, the severely broadened main-lobe clutter cannot be ignored, which will cause the deterioration of the moving target ...
Penghui Huang +4 more
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Application of AMD Versal™ Adaptive SoC to Radar Space Time Adaptive Processing in Space
2023 European Data Handling & Data Processing Conference (EDHPC), 2023Space Time Adaptive Processing (STAP) radar systems require rapid execution of complex matrix multiplications to calculate and apply covariances and adaptive filtering weights, to achieve filtering of ground clutter and to mitigate jamming. Developers of
Jason Timpe +5 more
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Space-Time Adaptive Processing via Random Matrix Theory for Finite Training Samples
IEEE Sensors Journal, 2023Space-time adaptive processing (STAP) is one of the most effective approaches for clutter suppression in airborne radar systems. However, when the number of training samples is less than two times system degrees of freedom (DoFs), the performance of ...
Di Song +3 more
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IEEE Transactions on Aerospace and Electronic Systems, 2023
This correspondence discusses a space–time adaptive processing (STAP) method using deep neural network (DNN) and shrinkage algorithm (SA) under small training samples. A DNN-based SA is developed to estimate the clutter-plus-noise covariance matrix (CNCM)
Di Song +4 more
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This correspondence discusses a space–time adaptive processing (STAP) method using deep neural network (DNN) and shrinkage algorithm (SA) under small training samples. A DNN-based SA is developed to estimate the clutter-plus-noise covariance matrix (CNCM)
Di Song +4 more
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A Parametric Approach to Space-Time Adaptive Processing in Bistatic Radar Systems
IEEE Transactions on Aerospace and Electronic Systems, 2022Space-time adaptive processing (STAP) is an important airborne radar technique used to improve target detection in environments of clutter and jammers.
Jacob Klintberg, T. McKelvey, P. Dammert
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Single-Channel Anti-Jamming Receiver With Harmonic-Based Space-Time Adaptive Processing
IEEE Wireless Communications Letters, 2022A novel anti-jamming receiver with harmonic-based space-time adaptive processing (STAP) is presented. In radio frequency (RF) front, a 1-bit time-modulated array (TMA) is deployed to modulate the received signals periodically, indicating that only one RF
Gang Ni, Chong He, R. Jin
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Space-time Adaptive Processing via Fast Environment Sensing
International Conference on Signal Processing, Communications and Computing, 2022In the heterogeneous clutter environment, the traditional space-time adaptive processing (STAP) cannot accurately estimate the clutter covariance matrix (CCM) due to the lack of training samples, so its clutter suppression performance is seriously ...
Youai Wu +3 more
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