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

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Author(s)Zou, Zihao
Author(s)Xia, Xiang-Gen
Author(s)Liu, Xingzhao
Author(s)Liao, Guisheng
Date Accessioned2022-03-16T20:14:11Z
Date Available2022-03-16T20:14:11Z
Publication Date2022-01-21
DescriptionCopyright 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This article was originally published in IEEE Transactions on Geoscience and Remote Sensing. The version of record is available at: https://doi.org/10.1109/TGRS.2022.3144668en_US
AbstractWhen 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.en_US
SponsorThis work was supported in part by the National Natural Science Foundation Program of China under Grant 62171272, in part by USCAST2021, and in part by SAST2019-071.en_US
CitationP. Huang, Z. Zou, X. -G. Xia, X. Liu and G. Liao, "A Novel Dimension-Reduced Space–Time Adaptive Processing Algorithm for Spaceborne Multichannel Surveillance Radar Systems Based on Spatial–Temporal 2-D Sliding Window," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-21, 2022, Art no. 5109721, doi: 10.1109/TGRS.2022.3144668.en_US
ISSN1558-0644
URLhttps://udspace.udel.edu/handle/19716/30664
Languageen_USen_US
PublisherIEEE Transactions on Geoscience and Remote Sensingen_US
KeywordsClutter suppressionen_US
Keywordsdimension-reduced STAPen_US
Keywordsearly warning surveillance radaren_US
Keywordsspace–time adaptive processing (STAP)en_US
TitleA Novel Dimension-Reduced Space–Time Adaptive Processing Algorithm for Spaceborne Multichannel Surveillance Radar Systems Based on Spatial–Temporal 2-D Sliding Windowen_US
TypeArticleen_US
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