An interacting multiple models probabilistic data association algorithm for maneuvering target tracking in clutter

DOI

10.2991/isci-15.2015.225How to use a DOI?

Keywords

Target tracking; Debiased converted measurement; Probabilistic data association; Interacting multiple model; Clutter

Abstract

To solve the problem of tracking maneuvering target in the presence of clutter, the debiased converted measurement based interacting multiple model (IMMDCM) estimator in combination with the probabilistic data association (PDA) technique is proposed for airborne target tracking. Under the architecture of the proposed algorithm, the IMM deals with the model switching, the debiased converted measurement filter accounts for non-linearity in the dynamic system models, while the PDA handles data association and measurement uncertainties in clutter. The simulation results show that the proposed algorithm can improve the tracking precision for maneuvering target in clutters, and has higher tracking precision than the traditional IMMEKF based PDA algorithm.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xingxiu Li
AU  - Panlong Wu
AU  - Xinyu Zhang
PY  - 2015/01
DA  - 2015/01
TI  - An interacting multiple models probabilistic data association algorithm for maneuvering target tracking in clutter
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 1685
EP  - 1692
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.225
DO  - 10.2991/isci-15.2015.225
ID  - Li2015/01
ER  -