Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking

Published

Journal Article

© 2014 IEEE. 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.

Full Text

Duke Authors

Cited Authors

  • Foderaro, G; Zhu, P; Wei, H; Wettergren, TA; Ferrari, S

Published Date

  • March 1, 2018

Published In

Volume / Issue

  • 5 / 1

Start / End Page

  • 142 - 153

International Standard Serial Number (ISSN)

  • 2325-5870

Digital Object Identifier (DOI)

  • 10.1109/TCNS.2016.2583070

Citation Source

  • Scopus