RADAR HRRP RECOGNITION BASED ON THE MINIMUM KULLBACK-LEIBLER DISTANCE CRITERION  

作　　者：Yuan Li Liu Hongwei Bao Zheng 

机构地区：[1]Key Lab for Radar Signal Processing, Xidian University, Xi＇an 710071, China

出　　处：《Journal of Electronics(China)》2007年第2期199-203,共5页电子科学学刊（英文版）

基　　金：Partially supported by the National Natural Science Foundation of China (No.60302009).

摘　　要：To relax the target aspect sensitivity and use more statistical information of the High Range Resolution Profiles (HRRPs), in this paper, the average range profile and the variance range profile are extracted together as the feature vectors for both training data and test data representa-tion. And a decision rule is established for Automatic Target Recognition (ATR) based on the mini-mum 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 efficient. Experimental results based on the measured data show that the minimum KLD classifier is effective.To relax the target aspect sensitivity and use more statistical information of the High Range Resolution Profiles （HRRPs）, in this paper, the average range profile and the variance range profile are extracted together as the feature vectors for both training data and test data representation. And a decision rule is established for Automatic Target Recognition （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 efficient. Experimental results based on the measured data show that the minimum KLD classifier is effective.

关 键 词：High Range Resolution Profile （HRRP） Automatic Target Recognition （ATR） Kullback-Leibler Distance （KLD） Adaptive Gaussian Classifier （AGC） 

分 类 号：TN957.52[电子电信—信号与信息处理]