Maneuver Strategy Adaptive Target Tracking Algorithm by Integrated Kalman Information Filtering

This article introduces the concept of maneuver strategy and its transition probability matrix, and then builds a target tracking model with multi-motion and multi-maneuver strategy model based on these concepts in order to resolve the problem of undesired tracking performance especially when unexpected maneuver strategy changes of target occurs. To achieve further improvements in tracking accuracy, a self-adaptive algorithm for maneuver strategy transition probability matrix is proposed in this article, by utilizing the compression ratio of the maneuver strategy error. Besides, considering that most of the observation platforms are already able to provide multi-group measurements from different sensors, information filtering is combined in this article to fuse and integrate multi-group measurements, thus effectively improving estimation stability and ameliorating the inevitable soaring estimation error through target's unexpected changes of maneuver strategy.