Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

: We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs). Three different (PFs) are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS) framework. The proposed filters are (i) multiple mode...

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Bibliographic Details
Published inEURASIP journal on advances in signal processing Vol. 2004; no. 15; p. 562960
Main Authors Arulampalam, M Sanjeev, Ristic, B, Gordon, N, Mansell, T
Format Journal Article
LanguageEnglish
Published BioMed Central Ltd 07.11.2004
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Summary:: We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs). Three different (PFs) are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS) framework. The proposed filters are (i) multiple model PF (MMPF), (ii) auxiliary MMPF (AUX-MMPF), and (iii) jump Markov system PF (JMS-PF). The performance of these filters is compared with that of standard interacting multiple model (IMM)-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i) single-sensor case, (ii) multisensor case, and (iii) tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.
ISSN:1687-6180
1687-6180
DOI:10.1186/1687-6180-2004-562960