Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking

This paper presents a distributed optimal control approach for managing omnidirectional sensor networks deployed to cooperatively track moving targets in a region of interest. Several authors have shown that under proper assumptions, the performance of mobile sensors is a function of the sensor dist...

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Published inIEEE transactions on control of network systems Vol. 5; no. 1; pp. 142 - 153
Main Authors Foderaro, Greg, Pingping Zhu, Hongchuan Wei, Wettergren, Thomas A., Ferrari, Silvia
Format Journal Article
LanguageEnglish
Published IEEE 01.03.2018
Subjects
Distributed control
Mobile communication
mobile sensor networks
multiscale dynamical systems
Optimal control
Probability density function
Robot sensing systems
Target tracking
track coverage
Vehicles
Online AccessGet full text
ISSN2325-5870
2372-2533
DOI10.1109/TCNS.2016.2583070

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Abstract This paper presents a distributed optimal control approach for managing omnidirectional sensor networks deployed to cooperatively track moving targets in a region of interest. Several authors have shown that under proper assumptions, the performance of mobile sensors is a function of the sensor distribution. In particular, the probability of cooperative track detection, also known as track coverage, can be shown to be an integral function of a probability density function representing the macroscopic sensor network state. Thus, a mobile sensor network deployed to detect moving targets can be viewed as a multiscale dynamical system in which a time-varying probability density function can be identified as a restriction operator, and optimized subject to macroscopic dynamics represented by the advection equation. Simulation results show that the distributed control approach is capable of planning the motion of hundreds of cooperative sensors, such that their effectiveness is significantly increased compared to that of existing uniform, grid, random, and stochastic gradient methods.
AbstractList This paper presents a distributed optimal control approach for managing omnidirectional sensor networks deployed to cooperatively track moving targets in a region of interest. Several authors have shown that under proper assumptions, the performance of mobile sensors is a function of the sensor distribution. In particular, the probability of cooperative track detection, also known as track coverage, can be shown to be an integral function of a probability density function representing the macroscopic sensor network state. Thus, a mobile sensor network deployed to detect moving targets can be viewed as a multiscale dynamical system in which a time-varying probability density function can be identified as a restriction operator, and optimized subject to macroscopic dynamics represented by the advection equation. Simulation results show that the distributed control approach is capable of planning the motion of hundreds of cooperative sensors, such that their effectiveness is significantly increased compared to that of existing uniform, grid, random, and stochastic gradient methods.
Author Hongchuan Wei
Pingping Zhu
Wettergren, Thomas A.
Ferrari, Silvia
Foderaro, Greg
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Snippet This paper presents a distributed optimal control approach for managing omnidirectional sensor networks deployed to cooperatively track moving targets in a...
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StartPage 142
SubjectTerms Distributed control
Mobile communication
mobile sensor networks
multiscale dynamical systems
Optimal control
Probability density function
Robot sensing systems
Target tracking
track coverage
Vehicles
Title Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking
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