A comparative study of the Benes filtering problem

Authors:
A. Farina;D. Benvenuti;B. Ristic
Affiliations:
Alenia Marconi Systems, Systems Analysis Group, Via Tiburtina Km. 12.400, 00131 Rome, Italy;Alenia Marconi Systems, Systems Analysis Group, Via Tiburtina Km. 12.400, 00131 Rome, Italy;Surveillance Systems Division, Defence Science and Technology Organisation, P.O. Box 1500, Salisbury, SA 5108, Australia
Venue:
Signal Processing
Year:
2002

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Abstract

This paper studies a non-linear filter due to Benes for which the optimum solution is known. The paper compares the estimation performance of Benes filter to those of well-known approximate filters: the Extended Kalman, the statistical linearisation and the particle filtering. The performance of all these four filters are also compared to the Cramer-Rao lower bound. Thus, the Benes filter is a yardstick to rank the above-mentioned known techniques in terms of performance and computational cost which solve in an approximate manner the problem solved in an optimum way by Benes. This class of non-linear filtering problem has an interest in application problems like the target tracking.