DocumentCode
3260614
Title
Multi-radar tracking based on weighted k-means clustering fusion
Author
Zhang, Yi ; Liu, Hongchang ; Fu, Wenyong ; Deng, Haowen
Author_Institution
Res. Center of Intell. Syst. & Robot., Chongqing Univ. of Posts & Telecommun., Chongqing
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
813
Lastpage
816
Abstract
The application of data fusion technology is a research focus in the field of radar tracking. In this paper, weighted k-means clustering method is applied to distinguish the measurements data set of different objectives. Then, the measurements in the different cluster are fused by using kalman filter. The experiment shows that filtering track with k-means clustering fusion is closer to the real track than without clustering.
Keywords
Kalman filters; pattern clustering; radar tracking; sensor fusion; target tracking; data fusion technology; kalman filter; multiradar tracking; multitarget tracking; weighted k-means clustering fusion method; Clustering algorithms; Clustering methods; Delay; Filtering; Intelligent robots; Intelligent systems; Radar antennas; Radar measurements; Radar tracking; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-2512-9
Electronic_ISBN
978-1-4244-2513-6
Type
conf
DOI
10.1109/GRC.2008.4664635
Filename
4664635
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