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《Journal of Projectiles,Rockets,Missiles and Guidance》 2015-05
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An Adaptive Particle Local PHD Filter

TONG Qian;LI Hong Yan;WEI Zhang;MAO Shaofeng;Lu Chuanguo;Information and Navigation College,Air Force Engineering University;No.95806 Unit;  
Filter with standard particle probability assumption is of less accuracy and larger computation complexity. To solve the problem,an adaptive particle local PHD filter algorithm was proposed. The approach makes use of accelerate covariance to adjust adaptive gate,the size of which changes according to target movement condition. The object region and clutter region are separated,part of clutter eliminated,and particle PHD filter is performed in each region separately,with simulation at last. The simulation reveals that compared with standard PHD filter,the amount of calculation is reduced while the precision increases.
【CateGory Index】: TN713
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