Konferenční příspěvek

Straka O., Šimandl M., Duník J.

Preprints of the 12th International Conference on Information Fusion

Seattle, USA

2009

270-277

978-0-9824438-0-4

Ing. Jindřich Duník, Ph.D. (FAV Západočeská univerzita, katedra kybernetiky)

tracking, nonlinear filtering, estimation

clanek_FUSION09_JD.pdf [file]

prezentace_FUSION09_JD.pdf [file]

The paper deals with state estimation for the track-before-detect approach using the particle filter. The focus is aimed at the track initiation proposal density of the particle filter which considerably affects estimate quality. The goal of the paper is to design a proposal based on a Gaussian mixture using a bank of extended Kalman filters. This leads to root mean square error lower than that achieved by usual simple track initiation proposals. Due to application of several developed techniques reducing computational requirements of the designed proposal, the Gaussian mixture particle filter also achieves lower computational requirements than ordinary particle filter. Performance of the proposed Gaussian mixture track initiation proposal in the particle filter is demonstrated in a numerical example.