Open Access

Particle Filtering Algorithms for Tracking a Maneuvering Target Using a Network of Wireless Dynamic Sensors

EURASIP Journal on Advances in Signal Processing20062006:083042

Received: 16 June 2005

Accepted: 30 April 2006

Published: 27 June 2006


We investigate the problem of tracking a maneuvering target using a wireless sensor network. We assume that the sensors are binary (they transmit '1' for target detection and '0' for target absence) and capable of motion, in order to enable the tracking of targets that move over large regions. The sensor velocity is governed by the tracker, but subject to random perturbations that make the actual sensor locations uncertain. The binary local decisions are transmitted over the network to a fusion center that recursively integrates them in order to sequentially produce estimates of the target position, its velocity, and the sensor locations. We investigate the application of particle filtering techniques (namely, sequential importance sampling, auxiliary particle filtering and cost-reference particle filtering) in order to efficiently perform data fusion, and propose new sampling schemes tailored to the problem under study. The validity of the resulting algorithms is illustrated by means of computer simulations.


Authors’ Affiliations

Departamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid


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© J. Míguez and A. Artés-Rodríguez 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.