Title :
A novel measurement matrix optimization method for radar sparse imaging with OFDM-LFM signals
Author :
Yijun Chen;Xiaoyou Yang;Ziqiang Ma;Qun Zhang;Guozheng Wang
Author_Institution :
Institute of Information and Navigation, Air Force Engineering University, Collaborative Innovation Center of Information Sensing and Understanding, Xi´an, People´s Republic of China
Abstract :
Compressed Sensing (CS) has been widely used in radar imaging field to reduce the data amount. The measurement matrix has direct effect on the degree of dimension reduction and the quality of target image. However, the measurement matrix is usually chosen as random Gaussian matrix or local Fourier matrix, and the influence from target characteristics to the measurement matrix optimization has not been considered. In this paper, focuses on the OFDM-LFM signals, a novel measurement matrix optimization method for radar sparse imaging is proposed. In this method, genetic algorithm is used to implement the measurement matrix optimization by equaling the measurement matrix to the chromosome. And then the satisfied imaging result can be achieved with minimal measurement dimension by using the obtained optimal measurement matrix. Some simulation results illustrate the effectiveness of the proposed method.
Keywords :
"Imaging","Radar imaging","Sparse matrices","Genetic algorithms","Optimization","Matrix decomposition","Noise"
Conference_Titel :
Synthetic Aperture Radar (APSAR), 2015 IEEE 5th Asia-Pacific Conference on
DOI :
10.1109/APSAR.2015.7306236