A Maximum Likelihood Look-Ahead Unscented Rao-Blackwellised Particle Filter
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.
Authors who publish with Engineering Journal agree to transfer all copyright rights in and to the above work to the Engineering Journal (EJ)'s Editorial Board so that EJ's Editorial Board shall have the right to publish the work for nonprofit use in any media or form. In return, authors retain: (1) all proprietary rights other than copyright; (2) re-use of all or part of the above paper in their other work; (3) right to reproduce or authorize others to reproduce the above paper for authors' personal use or for company use if the source and EJ's copyright notice is indicated, and if the reproduction is not made for the purpose of sale.