NDLI: Method of adjoint particle filters in nonlinear Bayesian estimation problems with a high prior uncertainty

Content Provider	Springer Nature Link
Author	Arsenjev, D. G. Berkovskii, N. A.
Copyright Year	2015
Abstract	A modification of the widely known scheme for solving nonlinear Bayesian optimal estimation problems in which the state vector contains a parameter not varying during the estimation process is proposed. Such problems are often solved by a technique in which the varying part of the state vector is modeled using sequential Monte Carlo methods (particle filters) and the parameter is modeled as a conditional distribution associated with a specific trajectory (implementation of the moving component). Different modifications of this scheme differ mainly in the ways of modeling the parameter. In some recent works devoted to the problem of simultaneous localization and mapping, the vector parameter which consists of coordinates of unknown reference points (landmarks) is modeled using the generalized Kalman filter, Gaussian sum filters, and more specific methods. We consider a modification in which the parameter, as well as the moving part of the state vector, is modeled using particle filters. The main recurrence relationships between weights of particle filters are derived. The proposed computational algorithm is illustrated by an application to the problem of bearing-only simultaneous localization and mapping.
Starting Page	349
Ending Page	366
Page Count	18
File Format	PDF
ISSN	10642307
Journal	Journal of Computer and Systems Sciences International
Volume Number	54
Issue Number	3
e-ISSN	15556530
Language	English
Publisher	Pleiades Publishing
Publisher Date	2015-06-03
Publisher Place	Moscow
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Theoretical Computer Science Computer Networks and Communications Control and Systems Engineering Information Systems Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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