Sensor scheduling using a 0-1 mixed integer programming framework

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 0-1 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

Original languageEnglish (US)
Title of host publication2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
Pages471-475
Number of pages5
StatePublished - Dec 1 2006
Event4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 - Waltham, MA, United States
Duration: Jul 12 2006Jul 14 2006

Publication series

Name2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006

Other

Other4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
CountryUnited States
CityWaltham, MA
Period7/12/067/14/06

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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