A Novel Adaptive Estimator for Maneuvering Target Tracking

A new method for maneuvering target tracking using "current" statistical model is presented. When tracked target maneuver occurs, "current" statistical model can detect the maneuver immediately and estimate the maneuver value accurately, and then the tracking filter will be compensated correctly and duly by estimated maneuver value. Based on this model, an interacting multiple model (IMM) estimator with Kalman filter (KF) as filter module is developed. For evaluating the performance of the estimator, a maneuvering target scenario is included. Simulation results show that the performance is superior to the traditional IMM algorithms when target maneuver is considered, and the method also yields lower computational load.