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| A Novel Detection Method of Shallow Buried Objects with Sequence Images of the Vehicle-Mounted Forward-Looking GPSAR |
| Yang Yan-guang; Song Qian; Zhou Zhi-min; Jin Tian; Zhang Han-hua |
| School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China |
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Abstract Since the small Radar Cross Section (RCS) and complicated buried environments of shallow buried targets will lead to large numbers of false alarms in the detection results of single frame image, a novel detection method called as “prescreening-alternately backward tracking-multiframe confirmation” is proposed in this paper. Firstly, the prescreening of images is made by the Constant False Alarm Rate (CFAR) detector, then followed by a morphological filter and clustering analysis. Secondly, the clustering centers of the current frame range multi-look image are utilized to mark the potential targets for tracking, and a new alternately backward tracking method is used to obtain the potential object tracks. Finally, the tracks are employed to compute the weighted historical confidences, which are exploited to eliminate the natural clutters and confirm targets. Experimental results of the real data show that the proposed approach can acquire the regions of interest fast and robustly, reduce the false alarms obviously.
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Received: 28 April 2008
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2009, Vol. 31 
