iln atlaptive-gain 0-9 tracker cornbined with circular prediction for maneuvering target tracking is proposed as a nonlinear prediction filer. For track-while-scan systems using phased array antenna, the reduction of prediction error is ill1 very important issutr. The purpose of this scheme ir t o achieve good noise reduction and get better maneu-\ c:r-following capability. Simulation results for several targci profilcs arc. incliided for a comparison of the perfortniiiices of our proposed scheme with that of conventional I r i d i t i g filters.
Maneuvering targets are difficult to track for tihe Kalman filter since the target model of tracking filter might not fit the real barget trajectory and the stat,istical characteristics of t,he target maneuver are unknown in advance. In order to track such a heavy maiieuvering target, the est,iination of the target turndirection is necessary. T h e t,wo-stage estimator using advanced circular prediction which considers the ta.rget t,urn-direction is proposed for maneuvering target, tracking. Sirnulat,ion results are given for a comparison of the perfornimces of our proposed scheme with t>hat of c,onvent,ional t r x k i n g filkrs.
SUMMARYTarget tracking filters with a low computational load are desired in air traffic control systems in order to simultaneously search and track multiple aircraft. The applications of the α-β filter and the Kalman filter have been widely studied. Although excellent tracking accuracy can be obtained for linear motion by the α-β filter, the tracking accuracy degrades for a maneuvering target, the difference between the predicted position and the actual target position becomes large, and mistracking where the target is lost may occur. While there has been research on filters that estimate the acceleration, these filters could only be used when there is little maneuvering and the computational load is huge. In this research, we propose a method that adds an acceleration term during turning motion as the tracking filter for maneuvering motion and not just linear motion and estimates the turning acceleration from past estimated positions of the target. We also reduce the tracking errors for a maneuvering target. We use simple trajectories of the target in computer simulations and compare the proposed method to conventional filters to demonstrate its effectiveness. And we evaluate the performance of the proposed acceleration estimation method.
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