On marginal particle filters with linear complexity

Author

Gustafsson, Fredrik

Author_Institution

Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden

fYear

2013

fDate

15-18 Dec. 2013

Firstpage

356

Lastpage

359

Abstract

The choice of proposal distribution affects critically the efficiency of a particle filter (PF). When it is not feasible to increase the number of particles, then more advanced proposals may avoid particle depletion. One further option is to compute the marginal posterior distribution. However, exact marginalization has quadratic complexity in the number of particles. This contribution discusses and compares some ideas for implementing a marginal PF with linear complexity, leading to an accept-reject algorithm. However, it turns out that the proposed solution can be interpreted as a way to implement the optimal proposal. Different proposals with and without marginalization are compared on a simple example.

Keywords

computational complexity; particle filtering (numerical methods); accept-reject algorithm; linear complexity; marginal PF; marginal particle filters; marginal posterior distribution; quadratic complexity; Approximation methods; Complexity theory; Conferences; Monte Carlo methods; Proposals; Signal to noise ratio; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 IEEE 5th International Workshop on

Conference_Location

St. Martin

Print_ISBN

978-1-4673-3144-9

Type

conf

DOI

10.1109/CAMSAP.2013.6714081

Filename

6714081