Konferenční příspěvek

Straka O., Duník J., Šimandl M.

Proceedings of the 14th International Conference on Information Fusion (FUSION 2011)

Chicago, USA

2011

978-1-4577-0267-9

Ing. Ondřej Straka, Ph.D. (FAV Západočeská univerzita, katedra kybernetiky)

bearings-only tracking , nonlinear filtering , state estimat

clanek_fusion11_SDS2.pdf [file]

prezentace_fusion11_SDS2.pdf [file]

The paper deals with a performance analysis of several local filters within three bearing-only tracking scenarios. Performance of the extended Kalman filter, unscented Kalman filter, unscented Kalman filter with adaptive scaling parameter, which represent generic filters, and the shifted Rayleigh filter, which is designed solely for the bearing-only tracking problem, is compared using the root mean square error, averaged normalized estimation error squared and non-credibility index. The simulations show that the unscented Kalman filter with adaptive scaling parameter achieves similar or even better performance than the shifted Rayleigh filter.