In view of the significant spatial variance in the azimuth resolution of traditional spaceborne sliding spotlight SAR, this paper proposes a scanning strategy optimizing method for spaceborne squint sliding spotlight SAR based on particle swarm optimization. The proposed method can basically eliminate the spatial variance of azimuth resolution in SAR images and improve the accuracy of localization and identification when SAR images are used for target identification. Considering that traditional particle swarm optimization is prone to fall into local optimum when optimizing the scanning strategy, this paper proposes an improved particle swarm optimization in which a parameterized model of the sliding factor, whose parameters are solved using particle swarm optimization, is established and a neighborhood search algorithm is integrated so that the ability of the algorithm to reach the optimum is enhanced. Simulation results validate the effectiveness of the proposed method.
GONG Liwei
,
LI Fei
,
HAN Xiaodong
,
WANG Wei
. A Scanning strategy optimizing method for spaceborne squint sliding spotlight SAR based on particle swarm optimization[J]. Journal of University of Chinese Academy of Sciences, 2025
, 42(3)
: 361
-370
.
DOI: 10.7523/j.ucas.2023.056
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