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2009 | Vol. 35, no 1 | 23-30
Tytuł artykułu

Asynchronous distributed state estimation based on covariance intersection

Warianty tytułu
Języki publikacji
In this paper, the problem of state estimation in an asynchronous distributed multi-sensor system is considered. In such a system, the state of an object of interest is estimated by a group of local estimators. Each local estimator, based on a Kalman filter, performs fusion of data from its local sensor and other (local) processors to compute possibly best state estimates. In performing data fusion, however, two important issues need to be addressed: unknown correlation between data in local processors and the problem of asynchronism of local processors. In this paper, a multi-sensor asynchronous estimation algorithm is presented. The problem of unknown correlation is solved by a covariance intersection method. To deal with asynchronous data a continuous-time stochastic object model is introduced. Simulated experiments illustrate the effectiveness of the proposed approach.

Opis fizyczny
Bibliogr. 10 poz., wykr.
  • WETI (KSD), Gdańsk University of Technology, ul. Narutowicza 11/12, 80-952 Gdańsk, Poland,
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  • [7] Kowalczuk Z., Domżalski M., Covariance intersection method for distributed asynchronous multi-sensor state estimation, Proceedings of the 14th International Congress of Cybernetics and Systems of WOSC, Wrocław, CD-ROM, 2008, pp. 191-200.
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