Sensor Selection from Independence Graphs using Submodularity

Abstract

In this paper we develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary independence pattern, we construct a graph that denotes pairwise independence between sensors, which means those sensors can operate simultaneously. The set of all fully-connected sub graphs (cliques) of this independence graph can form a set of matroid constraints over which we maximize a sub modular objective function. Since we choose the objective function to be sub modular, the algorithm returns a near-optimal solution with approximation guarantees. We also argue that this framework generalizes to any network with a defined independence structure between sensors, and intuitively models problems where the goal is to gather information in a complex environment. We apply this framework to ping sequence optimization for active multistatic sonar arrays by maximizing sensor coverage and not only achieve significant performance gains compared to conventional round-robin sensors election, but approach optimal performance as well.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2017
Accession Number
AD1027381

Entities

People

  • David W. Krout
  • Les Atlas
  • Thomas R. Powers

Organizations

  • University of Washington

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computer Science
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • Fungi
  • Monte Carlo Method
  • Networks
  • Numbers
  • Optimization
  • Physics Laboratories
  • Polynomials
  • Probability
  • Sensor Networks
  • Sonar Arrays
  • Target Detection

Readers

  • Distributed Systems and Data Platform Development
  • Graph Algorithms and Convex Optimization.
  • Sensor Fusion and Tracking Systems.