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
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;
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
DOI :
10.1109/GRC.2008.4664635
