An improved multi-target data association method for automotive radar is presented. The new approach is formulated using the association probabilities of the joint probabilistic data association (JPDA) filter. An optimal track-to-measurement data association is accomplished using the decision logic algorithm. Simulation results in heavily cluttered conditions show that the tracking accuracy of the proposed method is about 19% better than that of the JPDA filter.
New data association method for automotive radar tracking
01.10.2001
5 pages
Aufsatz (Zeitschrift)
Englisch
radar clutter , filtering theory , tracking filters , optimal track-to-measurement data association , probability , road vehicle radar , computer simulation results , target tracking , tracking accuracy , JPDA filter , association probabilities , automotive radar tracking , joint probabilistic data association filter , radar tracking , multi-target data association method , decision logic algorithm
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