Bearings-only tracking with particle filtering for joint parameter learning and state estimation
Published in 15th International Conference on Information Fusion, 2012
Recommended citation: Nemeth, C., Fearnhead, P., Mihaylova, L. and Vorley, D. (2012). "Bearings-only tracking with particle filtering for joint parameter learning and state estimation," 15th International Conference on Information Fusion, pp. 824-831. https://ieeexplore.ieee.org/abstract/document/6289887
This paper considers the problem of bearings only tracking of manoeuvring targets. A learning particle filtering algorithm is proposed which can estimate both the unknown target states and unknown model parameters. The algorithm performance is validated and tested over a challenging scenario with abrupt manoeuvres. A comparison of the proposed algorithm with the Interacting Multiple Model (IMM) filter is presented. The learning particle filter has shown accurate estimation results and improved accuracy compared with the IMM filter.