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

作     者：Yuan Li Liu Hongwei Bao Zheng Yuan Li Liu Hongwei Bao Zheng (Key Lab for Radar Signal Processing, Xidian University, Xi’an 710071, China)

作者机构：Key Lab for Radar Signal Processing Xidian University Xi＇an 710071 China 

出 版 物：《Journal of Electronics(China)》 (电子科学学刊（英文版）)

年 卷 期：2007年第24卷第2期

页      面：199-203页

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

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

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

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.