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Journal of Applied Remote Sensing

Modified reconstruction algorithm based on space-time adaptive processing for multichannel synthetic aperture radar systems in azimuth
Author(s): Xiaojiang Guo; Yesheng Gao; Kaizhi Wang; Xingzhao Liu
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Paper Abstract

A spectrum reconstruction algorithm based on space–time adaptive processing (STAP) can effectively suppress azimuth ambiguity for multichannel synthetic aperture radar (SAR) systems in azimuth. However, the traditional STAP-based reconstruction approach has to estimate the covariance matrix and calculate matrix inversion (MI) for each Doppler frequency bin, which will result in a very large computational load. In addition, the traditional STAP-based approach has to know the exact platform velocity, pulse repetition frequency, and array configuration. Errors involving these parameters will significantly degrade the performance of ambiguity suppression. A modified STAP-based approach to solve these problems is presented. The traditional array steering vectors and corresponding covariance matrices are Doppler-variant in the range-Doppler domain. After preprocessing by a proposed phase compensation method, they would be independent of Doppler bins. Therefore, the modified STAP-based approach needs to estimate the covariance matrix and calculate MI only once. The computation load could be greatly reduced. Moreover, by combining the reconstruction method and a proposed adaptive parameter estimation method, the modified method is able to successfully achieve multichannel SAR signal reconstruction and suppress azimuth ambiguity without knowing the above parameters. Theoretical analysis and experiments showed the simplicity and efficiency of the proposed methods.

Paper Details

Date Published: 16 September 2016
PDF: 13 pages
J. Appl. Rem. Sens. 10(3) 035022 doi: 10.1117/1.JRS.10.035022
Published in: Journal of Applied Remote Sensing Volume 10, Issue 3
Show Author Affiliations
Xiaojiang Guo, Shanghai Jiao Tong Univ. (China)
Yesheng Gao, Shanghai Jiao Tong Univ. (China)
Kaizhi Wang, Shanghai Jiao Tong Univ. (China)
Xingzhao Liu, Shanghai Jiao Tong Univ. (China)

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