Particle Filtering Algorithms for Tracking a Maneuvering Target Using a Network of Wireless Dynamic Sensors
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Particle Filtering Algorithms for Tracking a Maneuvering Target Using a Network of Wireless Dynamic Sensors ´ Joaqu´ın M´ıguez and Antonio Artes-Rodr´ ıguez Departamento de Teor´ıa de la Se˜nal y Comunicaciones, Universidad Carlos III de Madrid, Avenida de la Universidad 30, Legan´es, 28911 Madrid, Spain Received 16 June 2005; Revised 24 January 2006; Accepted 30 April 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. Copyright © 2006 J. M´ıguez and A. Art´es-Rodr´ıguez. 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.
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INTRODUCTION
Recently, there has been a surge of interest in the application of networks of wireless microsensors in diverse areas, including manufacturing, health and medicine, transportation, environmental monitoring, scientific instrumentation and others [1–3]. One common feature to these applications is that they involve the detection, classification, and tracking of signals, with the outstanding peculiarity that the large amounts of (possibly multimodal) data acquired by the sensors must be handled and integrated in order to perform the prescribed tasks [1]. Wireless sensor networks (WSN) are usually depicted as a collection of data-acquiring devices (sensors) and one or more fusion centers which are in charge of integrating the data to extract the information of interest. This paper deals with the problem of tracking a moving target over a region which is monitored by WSN [4]. As well as in most WSN applications, the main constraints are related to the network cost of deployment and operation. It is desirable that the sensors be inexpensive and, as a consequence, devices with limited processing capabilities are commonly used [4]. Moreover, stringent energy consumption restrictions must be met for the continued and reliable operation of networks consisting of battery-supported
sensors. In this respect, radio communication is a major power-consumer [5], so it should be
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