NDLI: Globally Optimized Power Allocation in Multiple Sensor Fusion for Linear and Nonlinear Networks

Content Provider	IEEE Xplore Digital Library
Author	Rashid, U. Hoang Duong Tuan Apkarian, P. Ha Hoang Kha
Copyright Year	1991
Abstract	The present paper is concerned with a sensor network, where each sensor is modeled by either a linear or nonlinear sensing system. These sensors team up in observing either static or dynamic random targets and transmit their observations through noisy communication channels to a fusion center (FC) for locating/tracking the targets. Physically, the network is limited by energy resource. According to the available sum power budget, we develop a novel technique for power allocation to the sensor nodes that enables the FC produce the best linear estimate in terms of the mean square error (MSE). Regardless of whether the sensor measurements are linear or nonlinear, the targets are scalar or vectors, static or dynamic, the corresponding optimization problems are shown to be semidefinite programs (SDPs) of tractable optimization and thus are globally and efficiently solved by any existing SDP solver. In other words, new tractably computational algorithms of distributed Bayes filtering are derived with full multisensor diversity achieved. Intensive simulation shows that these algorithms clearly outperform previously known algorithms.
Sponsorship	IEEE Signal Processing Society
Starting Page	903
Ending Page	915
Page Count	13
File Size	1359242
File Format	PDF
ISSN	1053587X
Volume Number	60
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resource management Approximation methods Tin Target tracking Sensors Covariance matrix Filtering unscented transformations Bayes filtering data fusion linear and nonlinear sensor network linear fractional transformation (LFT) power allocation semidefinite programming (SDP)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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