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Robust Filtering via Semidefinite Programming with...
Journal article

Robust Filtering via Semidefinite Programming with Applications to Target Tracking

Abstract

In this paper we propose a novel finite-horizon, discrete-time, time-varying filtering method based on the robust semidefinite programming (SDP) technique. The proposed method provides robust performance in the presence of norm-bounded parameter uncertainties in the system model. The robust performance of the proposed method is achieved by minimizing an upper bound on the worst-case varianceof the estimation error for all admissible systems. …

Authors

Li L; Luo Z-Q; Davidson TN; Wong KM; Boss E

Journal

SIAM Journal on Optimization, Vol. 12, No. 3, pp. 740–755

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Publication Date

1 2002

DOI

10.1137/s1052623499358586

ISSN

1052-6234