Tracking multiple maneuvering targets for automotive radar is a vital issue. To this end, a novel DS-UKGMPHD algorithm which combines diagraph switching (DS), unscented Kalman (UK) filter and Gaussian mixture probability hypothesis density (GMPHD) filter is proposed in this paper. The algorithm is capable of tracking a varying number of target cars detected by automotive radar with nonlinear measurement models in a cluttered environment. In addition, variable structure is used to accommodate various target motions in real world. Simulation results demonstrate the superiority of the presented algorithm to IMM-UKGMPHD filter in terms of estimation accuracy of both number and states.
"Novel Multi-Target Tracking Algorithm for Automotive Radar," Progress In Electromagnetics Research C,
Vol. 62, 35-42, 2016. doi:10.2528/PIERC15121802
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