KEYWORDS: Particles, Detection and tracking algorithms, Signal to noise ratio, Sensors, Particle filters, Tin, Digital filtering, Computer simulations, Data modeling, Target recognition
In this paper, a solution to the TENET nonlinear filtering challenge is presented. The proposed approach is based on particle filtering techniques. Particle methods have already been used in this context but our method improves over previous work in several ways: better importance sampling distribution, variance reduction through Rao-Blackwellisation etc. We demonstrate the efficiency of our algorithm through simulation.
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