Collaborative in-network processing for target tracking

  • Authors:
  • Juan Liu;James Reich;Feng Zhao

  • Affiliations:
  • Palo Alto Research Center, Palo Alto, CA;Palo Alto Research Center, Palo Alto, CA;Palo Alto Research Center, Palo Alto, CA

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2003

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Abstract

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.