Abstract
The two-stage alpha-beta-gamma estimator is proposed as an alternative to adaptive gain versions of the alpha, beta and alpha, beta, and gamma filters for tracking maneuvering targets. The aim is to achieve fixed-gain, variable dimension filtering. The two-stage alpha-beta-gamma estimator is derived from the two-stage Kalman estimator, and the noise variance 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 to compare the performances of other estimators with that of the alpha-beta-gamma filter. >
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