Abstract
Radar automatic target recognition (ATR) based on multiple high range resolution profiles (HRRPs) is concerned. To relax the target aspect sensitivity and use more statistical information of the HRRPs, in this paper we extract the average range profile and the variance range profile together as the feature vectors for both training data and test data representation. And a decision rule is established for ATR based on the minimum Kullback-Leibler distance (KLD) criterion. The recognition performance of the proposed method is comparable with that of adaptive Gaussian classifier (AGC) with multiple test HRRPs, but the proposed method is much more computational efficiently. Experimental results based on the measured data show the minimum KLD classifier is effective.
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