Particle filter based MAP state estimation: A comparison
Suman Saha, Yvo Boers, Johannes N. Driessen, Pranab Kumar Mandal, Arunabha Bagchi · University of Twente Research Information · 2009
MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi algorithm based MAP sequence estimator has been developed. In this paper, we compare these two methods for estimating the current state and the numerical results show that the former performs better.