摘要
A new modeling and filtering approach for tracking maneuvering targets is presented in thispaper.The approach,which makes optimal estimate for the model With the random variable possible,depends on random step modeling of target maneuvers.In the new model,the unknown targetacceleration is treated as a random variable and then estimated directly.A detector is designed tofind out the target maneuvers and the estimation algorithm will be restarted when the maneuvers oc-cur.Combination of three-dimention Kalman filter with a detector forms a tracker for maneuveringtargets.The new tracking scheme is easy to implement and its capability is illustrated in two trackingexamples in which the new approach is compared with Mooses’on the performance.
A new modeling and filtering approach for tracking maneuvering targets is presented in this paper.The approach,which makes optimal estimate for the model With the random variable possible, depends on random step modeling of target maneuvers.In the new model,the unknown target acceleration is treated as a random variable and then estimated directly.A detector is designed to find out the target maneuvers and the estimation algorithm will be restarted when the maneuvers oc- cur.Combination of three-dimention Kalman filter with a detector forms a tracker for maneuvering targets.The new tracking scheme is easy to implement and its capability is illustrated in two tracking examples in which the new approach is compared with Mooses'on the performance.
