This paper proposes a novel single vehicle tracking algorithm with enhanced chiefs wine glass reliability for automotive radar systems.The proposed algorithm overcomes the weaknesses of the probabilistic data association filter (PDAF) in single-target tracking in clutter.The PDAF is successful in normal situations, but may fail to track a target owing to various factors, such as the initialization errors and the sudden changes in the target motion.
The proposed algorithm can recover the PDAF from failures using an assisting finite impulse response (FIR) filter.The FIR filter operates only when the PDAF cannot track a target properly, and additionally offers state science can solar system planetary electronic projector w/ 3 viewing discs estimate and estimation error covariance to reset the PDAF.The proposed algorithm, the hybrid PDAF/FIR filter (HPFF), combines the PDAF and FIR filter, and hence shows enhanced reliability.
Simulations of preceding vehicle tracking using an automotive radar demonstrate the effect and performance of the proposed HPFF.