Measurement Matrix Optimization for ISAR Sparse Imaging Based on Genetic Algorithm
Authors:
- 27 October 2016
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Geoscience and Remote Sensing Letters
- Vol. 13 (12) , 1875-1879
Abstract
Inverse synthetic aperture radar sparse imaging based on compressive sensing has been widely researched. The measurement matrix significantly affects the performance of target imaging. In this letter, focus on the kind of signals that consist of several subpulses with stepped frequency, a measurement matrix optimization method based on genetic algorithm (GA), is proposed. The actual physical observation process is considered and the target characteristics are utilized to optimize the measurement matrix. Then, the expected imaging results can be obtained with minimum data using the optimized measurement matrix. Meanwhile, the orthogonal matching pursuit algorithm is improved for signal reconstruction, which can reduce the computation load significantly. The effectiveness of the proposed method is demonstrated by experiments.Keywords
Funding Information
- National Natural Science Foundation of China (61471386, 61571457)
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