The Compressed Sensing Method for Three-dimensional Imaging of FASAR in Low SNR Environment
The performance of sparse reconstruction of compressed sensing becomes worse in low signal-to-noise ratio (SNR) environment, and thus the quality of sparse three-dimensional imaging of FASAR is greatly reduced. In this paper, an improved compressed sensing algorithm based on Hough transform is presented by using the continuity of sparse coefficient vector in the original range and slant-range two-dimensional space and the line detection method of Hough transform, which improve the sparse reconstruction performance of compressed sensing effectively. The simulation results show that the proposed method can effectively realize the sparse three-dimensional imaging of FASAR in low SNR environment.