MMW Radar Data Clustering Optimization Method Based on Phase Continuity

In CFAR processing of millimeter wave radar data, due to the parameter selecting and other reasons, some target points, especially those belong to large objects but have weaker intensity, may be recognized as noise points. These objects may be divided into several categories by clustering algorithms...

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Bibliographic Details
Main Authors: Wang, Heyao, Qiao, Lingbo, Zhao, Ziran
Format: Conference Proceeding
Language:English
Subjects:
Azimuth
CA-CFAR
clustering algorithm
Merging
milimeter wave radar
Optimization methods
phase continuity
Sensitivity
Target recognition
Wireless communication
Wireless sensor networks
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Description
Summary:In CFAR processing of millimeter wave radar data, due to the parameter selecting and other reasons, some target points, especially those belong to large objects but have weaker intensity, may be recognized as noise points. These objects may be divided into several categories by clustering algorithms due to the lack of these points. This paper optimizes DBSCAN clustering results by taking use of the phase continuity of one object in the azimuth direction, merging the incorrectly separated targets into one single class without affecting the sensitivity of small target discrimination.
ISSN:2377-8512
DOI:10.1109/CSRSWTC56224.2022.10098305