Title :
Interacting Methods for Manoeuvre Handling in the GM-PHD Filter
Author_Institution :
Math. Inst., Univ. of Oxford, Oxford, UK
fDate :
10/1/2011 12:00:00 AM
Abstract :
Probability hypothesis density (PHD) filter implementations with jump Markov linear system (JMLS) manoeuvre handling are well known. A new derivation, following the method of the popular interacting multiple model (IMM) filter from single target tracking, is presented and is shown to be equivalent to existing implementations. The resulting filter is shown to reduce to the optimal Bayes solution for jointly estimating target state and motion mode in the single target, linear, and Gaussian case.
Keywords :
Bayes methods; Gaussian processes; Markov processes; filtering theory; target tracking; Gaussian mixture probability hypothesis density filter; interacting multiple model filter; jump Markov linear system manoeuvre handling; optimal Bayes solution; single target tracking; target motion mode; target state mode; Markov processes; Mathematical model; Maximum likelihood detection; Nonlinear filters; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2011.6034685
