Collaborative in-network processing for target tracking
type: Item
instance of: scholarly article
title: Collaborative in-network processing for target tracking
zbMATH Open document ID: 1065.94523
DOI: 10.1155/S111086570321204X
author: Juan Liu
author: James Reich
author: Feng Zhao
published in: EURASIP Journal on Applied Signal Processing
publication date: 2005-05-03T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 94A13
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 2163788
zbMATH Keywords: distributed Bayesian estimation
zbMATH Keywords: beamforming
zbMATH Keywords: mutual information
zbMATH Keywords: sensor network
zbMATH Keywords: tracking
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 2163788