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NCV Filter Design for Radar Tracking of Maneuvering Targets with LFM Waveforms

Modern radars employ linear frequency modulated (LFM) waveforms for target tracking as the range-Doppler coupling enables better track accuracy in range. When tracking maneuvering targets with a nearly constant velocity (NCV) Kalman filter, the selection of the process noise variance is complicated by the fact that the process errors are modeled as white Gaussian, while target maneuvers are deterministic or highly correlated in time. In recent years, the deterministic tracking index was introduced and used to develop a relationship between the maximum acceleration of the target and the process noise variance that minimizes the maximum mean squared error (MMSE) in position. A lower bound on the process noise variance was also expressed in terms of the maximum acceleration and deterministic tracking index. In this paper, the design methods for NCV Kalman filters are extended to radar tracking with linear frequency modulation (LFM) waveforms. The effectiveness of the design methods are confirmed via Monte Carlo simulations.