Title: RFCM FOR DATA ASSOCIATION AND MULTITARGET TRACKING USING 3D RADAR
Authors: Chan, Chun-Nien
Fung, Carrson C.
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
Keywords: Autonomous driving;ADAS;data association;multitarget tracking;regularized fuzzy c-means
Issue Date: 1-Jan-2018
Abstract: Performance of object classification using 3D automotive radar relies on accurate data association and multitarget tracking, which are greatly affected by data bias and proximity of objects to each other. A regularized fuzzy c-means (RFCM) algorithm is proposed herein to resolve the data association uncertainty problem that has shown to outperform the conventional FCM algorithm. The proposed method exploits results from the companion tracker to increase performance robustness. Simulation results using simulated and field data have proven the efficacy of the proposed method.
URI: http://hdl.handle.net/11536/150761
Journal: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Begin Page: 2621
End Page: 2625
Appears in Collections:Conferences Paper