Probability Hypothesis Density Filter Multitarget Track-Before-Detect Application
Xiqin Wang · Dianzi xuebao · 2011
Tracking-before-detection(TBD) is well suitable for radar detection and target tracking of low-observable objects.Probability hypothesis density(PHD) filter is regarded as an efficient solution to multitarget tracking problem.However,PHD filter is hard to use in multitarget TBD problem directly.By discussing the applicable model and hypothesis,a standard multitarget measurement model for TBD and Poisson noise are presented.Consequently,a PHD filter application to multitarget TBD problem,with analytical weighting coefficient,is deduced and can exploit the power of PHD fully.Numerical simulations show our approach has better performance than multitarget particle filter.