Targets Separation and Imaging Method in Sparse Scene Based on Cluster Result of Range Profile Peaks

This paper focuses on the synthetic aperture radar (SAR) imaging of space-sparse targets such as ships on the sea, and proposes a method of targets separation and imaging of sparse scene based on cluster result of range profile peaks. Firstly, wavelet de-noising algorithm is used to preprocess the original echo, and then the range profile at different viewing positions can be obtained by range compression and range migration correction. Peaks of the range profiles can be detected by the fast peak detection algorithm based on second order difference operator. Targets with sparse energy intervals can be imaged through azimuth compression after clustering of peaks in range dimension. What's more, targets without coupling in range energy interval and direction synthetic aperture time can be imaged through azimuth compression after clustering of peaks both in range and direction dimension. Lastly, the effectiveness of the proposed method is validated by simulations. Results of experiment demonstrate that space-sparse targets such as ships can be imaged separately and completely with a small computation in azimuth compression, and the images are more beneficial for target recognition.