Title :
Design of nearly constant velocity filters for radar tracking of maneuvering targets
Author_Institution :
Georgia Tech Res. Inst., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
When tracking maneuvering targets with conventional algorithms, the process noise standard deviation used in the nearly constant velocity Kalman filter is selected vaguely in relation to the maximum acceleration of the target. In recent years, the deterministic tracking index was introduced and used to develop a relationship between the maximum acceleration 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 developed. The process noise variance was expressed in terms of the maximum acceleration, duration of the maneuver in number of measurement periods, and deterministic tracking index. In this paper, the design methods for nearly constant velocity filters are extended from Cartesian measurements to polar or spherical measurements found in radar systems. The effectiveness of the design methods for radar tracking are confirmed via Monte Carlo simulations.
Keywords :
Kalman filters; Monte Carlo methods; acceleration; least mean squares methods; measurement systems; radar tracking; target tracking; MMSE; Monte Carlo simulations; cartesian measurements; constant velocity filters; deterministic tracking index; maneuvering target tracking; maximum mean squared error; measurement periods; nearly constant velocity Kalman filter; polar measurements; process noise standard deviation; process noise variance; radar systems; radar tracking; spherical measurements; target acceleration; Acceleration; Indexes; Kalman filters; Noise; Radar tracking; Target tracking; Kalman filtering; Target tracking; estimation; filter design; radar;
Conference_Titel :
Radar Conference (RADAR), 2012 IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4673-0656-0
DOI :
10.1109/RADAR.2012.6212285