@TechReport{ it:2013-015,
author = {Olov Ros{\'e}n and Alexander Medvedev},
title = {Parallel Recursive Bayesian Estimation on Multicore
Computational Platforms Using Orthogonal Basis Functions},
institution = {Department of Information Technology, Uppsala University},
department = {Division of Systems and Control},
year = {2013},
number = {2013-015},
month = aug,
abstract = {A method to solve the recursive Bayesian estimation
problem by making use of orthogonal series expansions of
the involved probability density functions is presented.
The coefficients of the expansion for the posterior density
are then calculated recursively via prediction and update
equations. The method has two main benefits: it provides
high estimation accuracy at a relatively low computational
cost and it is highly amenable to parallel implementation.
An application to a bearings-only tracking problem shows
that the proposed method performs with the same accuracy as
the particle filter but at a 24 times lower computational
cost. A parallel implementation on a shared-memory
multicore machine demonstrates that linear speedup in the
number of cores is achievable.}
}