A reduced-dimension post-Doppler STAP method based on tensor Tucker decomposition

Jingya Li; Zhiwei Yang; JiaJia Gou

doi:10.1117/12.2655354

2 November 2022 A reduced-dimension post-Doppler STAP method based on tensor Tucker decomposition

Jingya Li, Zhiwei Yang, JiaJia Gou

Proceedings Volume 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022); 124550K (2022) https://doi.org/10.1117/12.2655354
Event: International Conference on Signal Processing and Communication Security (ICSPCS 2022), 2022, Dalian, China

Abstract

Space-time adaptive processing (STAP) can effectively suppress the clutter, which plays an important role in ground moving target indication (GMTI). However, it is difficult to obtain sufficient training samples with an increase in the number of spatial channels and adaptive processor dimensions in large arrays, especially in a complex geomagnetic detection environment. Traditional reduced-dimension STAP methods cannot offer significant benefits in real data processing in this issue. Thus, in this paper, a reduced-dimension post-Doppler STAP method based on tensor Tucker decomposition is proposed. Firstly, the distribution characteristics of the clutter spectrum in the post-Doppler domain are analyzed. Then, the feature spaces of beam and Doppler are extracted by tensor Tucker decomposition. Finally, the data dimension is reduced by the feature spaces, and clutter suppression is carried out. The results of the experiments based on real measured data demonstrate that the proposed method can achieve good performance with fewer samples than traditional methods.

Citation Download Citation

Jingya Li, Zhiwei Yang, and JiaJia Gou "A reduced-dimension post-Doppler STAP method based on tensor Tucker decomposition", Proc. SPIE 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022), 124550K (2 November 2022); https://doi.org/10.1117/12.2655354

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KEYWORDS

Doppler effect

Digital filtering

Signal to noise ratio

Spatial frequencies

Radar

Filtering (signal processing)

Target detection

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