Approach of Radar Target Recognition Based on Multiple Polarization Features Fusion
一种融合多极化特征的雷达目标识别方法

Aiming at the problem of a dramatic increase in data of multi-polarized high resolution range profile (HRRP) target recognition, a recognition algorithm based on low-dimension time-shift invariant feature vectors and dynamic combination of multiple classifiers was proposed. In this algorithm, firstly three on}dimension features of single-polarized HRRP sequence arc extracted to form the timcshift invariant feature vectors, and then a general classifier combination by dynamic ensemble of multiple classifiers is achieved, which is used to classify. Finally, the classification results of four singlcpolarized HRRPs arc assembled by weighted voting method. hhc result of experiment indicates that the algorithm not only reduces the size of the data, but also uses polarization information effectively to acquire higher correct recognition rate.