274 A Novel Measurement Matrix Design for Weather Radar Based on Compressive Sensing

Thursday, 31 August 2017
Zurich DEFG (Swissotel Chicago)
Qiangyu Zeng, Chengdu Univ. of Information Technology, Chengdu, China; and C. V. Chandra, J. He, X. Li, and H. Wang

Abstract: Weather radar signal processing using compressive sensing results in hardware simplification, enhances resolution, reduces data storage. Measurement matrix decides the sampling rate of system and affect the reconstructive signal quality. This paper considers the reconstruction process of weather radar signal, proposes optimization algorithm based on the singular value decomposition of measurement matrix, simulates actual echo data measured by weather radar and compares the reconstruction results between using random measurement matrix and using certainty measurement matrix. The results show that optimized measurement matrices reconstructed raw echo signal with high quality under lower sampling rate.
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