Fixed-gain two-stage estimators for tracking maneuvering targets

W.D. Blair
1993 IEEE Transactions on Aerospace and Electronic Systems  
FOREWORD The classical problem of weapons control involves predicting the future position of a maneuvering target. Critical to successful prediction is the accurate estimation of the current target state. With the advent of guided weapons, the consequences of threat maneuver are reduced when accurate estimates of the target state can be obtained. Threat trends indicate that the conditions under vhi.i hostile targets can be engaged successfully are becoming more difficult to achieve; hence, any
more » ... chieve; hence, any improvement in existing estimation algorithms is of critical importance. This report presents the results of an investigation of an approach to the improvement of an important class of target tracking algorithms. The work was supported by the Naval Surface Warfare Center Dahlgren Division (NSWCDD) AEGIS Program Office. ABSTRACT The two-stage Alpha-Beta-Gamma estimator is proposed as an alternative to adaptive gain versions of the Alpha-Beta and Alpha-Beta-Gamma filters for tracking maneuvering targets. The purpose of this report is to accomplish 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 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 twostage 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. iii
doi:10.1109/7.220947 fatcat:sc2yht5fcrdajmetflbwlt5wuq