Tensor-Based Sparse Recovery Space-Time Adaptive Processing for Large Size Data Clutter Suppression in Airborne Radar

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. In practice, a coarse space-time grids will bring a...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems 2023-04, Vol.59 (2), p.907-922
Hauptverfasser:	Cui, Ning, Xing, Kun, Yu, Zhongjun, Duan, Keqing
Format:	Artikel
Sprache:	eng
Schlagworte:	Airborne radar Bayes methods Clutter clutter suppression Complexity Dictionaries Estimation Finite element method Machine learning Mathematical analysis Performance degradation Radar equipment Space-time adaptive processing Spacetime sparse recovery space-time adaptive processing (SR-STAP) tensor processing Tensors Training
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