New Compressed Sensing ISAR Imaging Algorithm Based on Log–Sum Minimization

Ping, Cheng; Jiaqun, Zhao

doi:10.1515/jee-2016-0064

Abstract

To improve the performance of inverse synthetic aperture radar (ISAR) imaging based on compressed sensing (CS), a new algorithm based on log-sum minimization is proposed. A new interpretation of the algorithm is also provided. Compared with the conventional algorithm, the new algorithm can recover signals based on fewer measurements, in looser sparsity condition, with smaller recovery error, and it has obtained better sinusoidal signal spectrum and imaging result for real ISAR data. Therefore, the proposed algorithm is a promising imaging algorithm in CS ISAR.

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New Compressed Sensing ISAR Imaging Algorithm Based on Log–Sum Minimization

Abstract

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