This article is part of the series Sensor Networks.

Open Access Research Article

Collaborative In-Network Processing for Target Tracking

Juan Liu*, James Reich and Feng Zhao

Author Affiliations

Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA 94304, USA

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EURASIP Journal on Advances in Signal Processing 2003, 2003:616720  doi:10.1155/S111086570321204X

The electronic version of this article is the complete one and can be found online at:

Received:21 December 2001
Revisions received:4 October 2002
Published:30 March 2003

© 2003 Copyright © 2003 Hindawi Publishing Corporation

This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

sensor network; target tracking; distributed processing; Bayesian filtering; beamforming; mutual information

Research Article