Filtering and smoothing in the presence of outliers using duality and relaxed dynamic programming

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Abstract

In this paper we pose the state estimation problem for linear systems with Gaussian noise and disturbances and independently distributed measurements outliers as that of finding the joint a posteriori most probable (JAPMP) state and outlier sequence given the observations. We show that this problem can be reformulated as an optimal reference tracking problem for switched linear systems, which we call the dual problem. By using techniques from optimal and approximate control of switched linear systems we are able to solve this computationally challenging problem in an attractive manner. In particular, we can provide state estimators which guarantee to be within a constant likelihood factor from the optimal as well as state estimators which guarantee a better likelihood than that of other, suboptimal state estimators.

Original languageEnglish
Title of host publication58th IEEE Conference on Decision and Control (CDC 2019)
PublisherInstitute of Electrical and Electronics Engineers
Pages6038-6043
Number of pages6
ISBN (Electronic)9781728113982
DOIs
Publication statusPublished - 12 Mar 2020
Event58th IEEE Conference on Decision and Control (CDC 2019) - Nice, France
Duration: 11 Dec 201913 Dec 2019
https://cdc2019.ieeecss.org/

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2019-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference58th IEEE Conference on Decision and Control (CDC 2019)
Abbreviated titleCDC 2019
Country/TerritoryFrance
CityNice
Period11/12/1913/12/19
Internet address

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