HRRP multi-target recognition in a beam using prior-independent DBSCAN clustering algorithm

During the operation of monopulse radar, the high-resolution range profiles (HRRPs) of multiple targets may be overlapped, which will reduce the target recognition performance. In this study, a novel multi-target recognition method is proposed based on prior-independent density-based spatial cluster...

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Veröffentlicht in:	IET radar, sonar & navigation Jg. 13; H. 8; S. 1366 - 1372
Hauptverfasser:	Guo, Peng-cheng, Liu, Zheng, Wang, Jing-jing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 01.08.2019
Schlagworte:	high‐resolution range profiles HRRP multitarget recognition monopulse radar multiple targets noise algorithm pattern clustering PI‐DBSCAN algorithm prior‐independent DBSCAN clustering algorithm radar computing radar resolution radar signal processing radar target recognition radial distance‐azimuth plane Research Article support vector machine classifier support vector machines SVM classifier target motion target recognition performance test multitarget HRRP test phase training phase training samples test multitarget HRRP PI-DBSCAN algorithm HRRP multitarget recognition support vector machines support vector machine classifier radar signal processing monopulse radar target motion radar computing prior-independent DBSCAN clustering algorithm pattern clustering radar resolution radar target recognition high-resolution range profiles training samples radial distance-azimuth plane test phase target recognition performance training phase multiple targets SVM classifier noise algorithm
ISSN:	1751-8784, 1751-8792
Online-Zugang:	Volltext
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