A Novel Dimension-Reduced Space-Time Adaptive Processing Algorithm for Spaceborne Multichannel Surveillance Radar Systems Based on Spatial-Temporal 2-D Sliding Window

• Published in: IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-21
• Main Authors: Huang, Penghui, Zou, Zihao, Xia, Xiang-Gen, Liu, Xingzhao, Liao, Guisheng
• Format: Article
• Language: English
• Subjects: Adaptive algorithms; Algorithms; Clutter; Clutter suppression; Complexity; Computational complexity; Computer applications; dimension-reduced STAP; Dimensions; Doppler radar; Doppler sonar; Early warning radar; early warning surveillance radar; Echoes; Feasibility studies; Flight; Fourier transforms; Information processing; Localization; Low altitude; Moving targets; Radar; Radar antennas; Radar clutter; Radar data; Radar equipment; Sliding; Slumping; Space-time adaptive processing; Spaceborne radar; space–time adaptive processing (STAP); Spatiotemporal data; Surveillance; Surveillance radar; Target detection; Training
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2022.3144668

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 detection capability. To deal with this problem, a space-time adaptive processing (STAP) technique is proposed for effective clutter suppression based on the spatial-temporal 2-D joint filtering. However, the full-dimensional optimal STAP encounters the challenges of high computational complexity and large training sample requirement. Therefore, the dimension-reduced STAP technique becomes necessary. This article proposes a novel dimension-reduced STAP algorithm based on spatial-temporal 2-D sliding window processing. First, several sets of spatial-temporal data are obtained by using spatial-temporal 2-D sliding window. Then, for each set of data, the 2-D discrete Fourier transform is performed to transform the echo data into the angle-Doppler domain. Finally, jointly adaptive processing is performed to realize the clutter suppression. Compared with the conventional STAP algorithms, the improvements of this method over the existing methods are: 1) the proposed method requires fewer training samples due to the 2-D localization processing and 2) the proposed method can obtain the better clutter suppression performance with lower computational complexity. The feasibility and effectiveness of the proposed algorithm are verified by both simulated and real-measured multichannel surveillance radar data.