A CS-Jerk Model for Tracking Highly Maneuvering Targets

Jerk model for tracking highly maneuvering targets is investigated. Through theoretical analysis, it is shown that the filter, based on jerk model, may suffer from deterministic steady state estimation errors. To find the solution to this question, a current statistic Jerk model, for a short CS Jerk, is developed, in which the jerk maneuvering is assumed to be an exponential correlated random process with nonzero mean. It consists of a CS Jerk model of target motion and a tracking filter with compatible order. The steady state performance of the CS Jerk model is also analyzed and the result indicates that the CS Jerk model eliminates the performance limitation of the jerk model. The improved performance of the CS Jerk model over the jerk model is illustrated through simulation.