A Maximum Likelihood Look-Ahead Unscented Rao-Blackwellised Particle Filter

  • Peerapol Yuvapoositanon Mahanakorn University of Technology

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Abstract

A new maximum likelihood technique for the look-ahead unscented Rao-Blackwellised particle filter (la-URBPF) to improve its robustness to noise is proposed in this paper. A radial basis function whose centre is at the state associated with the maximum likelihood is also used for masking lower likelihood states without destroying information embedded in low prior states. Simulation results show how the proposed maximum likelihood la-URBPF algorithm responds to various noise levels ranging from relatively low to aggressively high levels. The computational times for different noise levels of the proposed algorithm are also investigated to assess its applicability in time-critical or in resource-restricted embedded systems.

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Author Biography
Peerapol Yuvapoositanon

Centre of Electronic Systems Design and Signal Processing (CESdSP), Faculty of Engineering, Mahanakorn University of Technology, 140 Cheumsamphan Road, Nong-Chok, Bangkok 10530, Thailand

Published
Vol 21 No 6, Oct 31, 2017
How to Cite
P. Yuvapoositanon, “A Maximum Likelihood Look-Ahead Unscented Rao-Blackwellised Particle Filter”, Engineering Journal (Eng. J.), vol. 21, no. 6, pp. 47-56, Oct. 2017.

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