Title :
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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288456
