On Robust Recognition Of Radar High Range Resolution Profiles In Noise Background

Radar Automatic Target Recognition is to identify the unknown target from its radar echoed signatures. With the development of the technology, it has made it possible for the radar to perform not only the classical tasks of detection, location, searching and tracking. In recent years, radar automatic target recognition has received intensive attention.As we know , radar target recognition contains more uncertainty, this is mainly because the target features is not only relative to the size of the target and radar parameter ,but also to the environment features as well. Therefore, it is more important to get a more robust classifier under different circumstance, this dissertation does some research and analysis on this background.This dissertation summarize the feature-abstracting and classification algorithms in radar HRRP, and make some researches to prove the classifiers'robust to noise, we divide this paper into two main parts: firstly, introduce the physics characteristic and pretreatment methods of radar HRRP, then summarize the feature-abstracting methods of it. Secondly, introduce several main classifiers in radar HRRP and research the classifiers'robust to noise by the experimental results.