Cooperative particle filtering for emitter tracking with unknown noise variance

Author

Dias, Stiven S. ; Bruno, Marcelo G S

Author_Institution

Embraer S.A., São José dos Campos, Brazil

fYear

2012

fDate

25-30 March 2012

Firstpage

2629

Lastpage

2632

Abstract

We introduce in this paper a novel cooperative particle filter algorithm for tracking a moving emitter using received-signal strength (RSS) measurements with unknown observation noise variance. In the studied scenario, multiple RSS sensors passively observe independently attenuated and perturbed versions of the same broadcast signal transmitted by an emitter which is moving through the sensor field and cooperate to estimate the emitter state. The new algorithm differs from previous methods by employing a parametric approximation to reduce the associated communication burden.

Keywords

particle filtering (numerical methods); tracking; RSS measurements; cooperative particle filtering; emitter state; emitter tracking; moving emitter; multiple RSS sensors; parametric approximation; received-signal strength; sensor field; unknown noise variance; unknown observation noise variance; Approximation algorithms; Approximation methods; Covariance matrix; Distributed algorithms; Particle filters; Sensors; Speech; Distributed Algorithms; Emitter Tracking; Particle Filters; RSS; Wireless Sensor Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Conference_Location

Kyoto

ISSN

1520-6149

Print_ISBN

978-1-4673-0045-2

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2012.6288456

Filename

6288456