Fixed-Gain, Two-Stage Estimators for Tracking Maneuvering Targets

摘要

The two-stage Alpha-Beta-Gamma estimator is proposed as an alternative toadaptive gain versions of the Alpha-Beta and Alpha-Beta-Gamma filters for tracking maneuvering targets. This report accomplishes fixed-gain, variable dimension filtering with a two-stage Alpha-Beta-Gamma estimator. The two-stage Alpha-Beta-Gamma estimator is derived from the two-stage Kalman estimator, and the noise variance and reduction matrix and steady-state error covariance matrix are given as a function of the steady-state gains. A procedure for filter parameter selection is also given along with a technique for maneuver response and a gain scheduling technique for initialization. The kinematic constraint for constant speed targets is also incorporated into the two-stage estimator to form the two-stage Alpha-Beta-Gamma-Lambda estimator. Simulation results are given for a comparison of the performances of estimators with that of the Alpha-Beta-Gamma filter. Kalman Estimator, Filters, Alpha-Beta-Filters, Alpha-Beta-Gamma Filters, Steady-State Filers, Target Tracking.