Hybrid PDA/FIR Filtering for Preceding Vehicle Tracking Using Automotive Radars

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