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Sensor Scheduling using a 0-1 Mixed Integer Programming Framework

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3 Author(s)
Chhetri, A.S. ; Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ ; Morrell, D. ; Papandreou-Suppappola, A.

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

Published in:

Sensor Array and Multichannel Processing, 2006. Fourth IEEE Workshop on

Date of Conference:

12-14 July 2006