Double Bayesian Smoothing as Message Passing
Abstract
Recently, a novel method for developing filtering algorithms, based on the interconnection of two Bayesian filters and called double Bayesian filtering, has been proposed. In this manuscript we show that the same conceptual approach can be exploited to devise a new smoothing method, called double Bayesian smoothing. A double Bayesian smoother combines a double Bayesian filter, employed in its forward pass, with the interconnection of two backward information filters used in its backward pass. As a specific application of our general method, a detailed derivation of double Bayesian smoothing algorithms for conditionally linear Gaussian systems is illustrated. Numerical results for two specific dynamic systems evidence that these algorithms can achieve a better complexity-accuracy tradeoff and tracking capability than other smoothing techniques recently appeared in the literature.
Cite
@article{arxiv.1907.11547,
title = {Double Bayesian Smoothing as Message Passing},
author = {Pasquale Di Viesti and Giorgio M. Vitetta and Emilio Sirignano},
journal= {arXiv preprint arXiv:1907.11547},
year = {2019}
}
Comments
arXiv admin note: text overlap with arXiv:1902.05717 and arXiv:1907.01358