Abstract: Due to the target-aspect sensitivity of high resolution rang profiles (HRRPs), we first use a modified k-nearest neighbor (KNN) rule for binary-class classification problem, and then extend it to multi-class classification problems using the one against one (OAO) method. This method adjusts the effective influence size of each training sample in order to make sure the statistical confidence level in a range that can be trusted. Experimental results show our method’s good performance for multi-class classification problems and its effectiveness to improve the KNN rule.

Key words: high resolution range profile(HRRP), the k-nearest neighbor (KNN) rule, radar automatic target recognition(RATR), targe-aspect sensitivity, one against one(OAO)