Fast Target Detection for SAR Images Based on Weighted Parzen-Window Clustering Algorithm
To solve the inefficiencies and high false alarm probability problem of the target detection in synthetic aperture radar (SAR) images and to improve the weakness of the two-parameter CFAR detector, a fast constant false alarm rate(CFAR) algorithm based on Weighted Parzen-window clustering (WPWC) is proposed. The principles and flow of the WPWC algorithm is introduced and a fast two parameter CFAR detector taking WPWC as a preprocessing, which reduced the effect of clutter and eliminated many false target detections from background. According to the theoretical performance analysis and the experiment results of some typical SAR images, the proposed algorithm is shown to be of good performance and strong practicability. Meanwhile, the corresponding fast algorithm greatly reduces the computational load.
component Weighted Parzen-Window clustering algorithm synthetic aperture radar(SAR) imagery target detection constant false alarm rate
Huiyan Liu
School of Science, National University of Defense Technology Changsha, 410073, China
国际会议
南宁
英文
164-167
2010-10-13（万方平台首次上网日期，不代表论文的发表时间）