Optimal Planning of Distributed Sensor Layouts for Collaborative Surveillance

Abstract

The use of a spatially distributed set of sensors has become a cost-effective approach to achieve surveillance coverage against moving targets. As more sensors are utilized in a collaborative manner, the optimal placement of sensors becomes critical to achieve the most efficient coverage. In this paper, we develop a numerical optimization approach to place distributed sets of sensors to perform surveillance against moving targets over extended areas. In particular, we develop a genetic algorithm solution to find spatial sensor density functions that maximize effectiveness against moving targets, where the surveillance performance of individual sensors is dependent on their absolute position in the region as well as their relative position to both the expected target(s) and any asset that is being protected. The density function representation of optimal sensor locations is shown to provide a computationally efficient method for determining sensor asset location planning. We illustrate the effective performance of this method on numerical examples based on problems of general area surveillance and risk-based surveillance in protection of an asset.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 01, 2013
Source ID
10.1155/2013/145496

Entities

People

  • Russell Costa
  • Thomas Wettergren

Organizations

  • Naval Undersea Warfare Center
  • Office of Naval Research

Tags

Fields of Study

  • Engineering

Readers

  • Inertial Navigation Systems.
  • Missile Defense Systems.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Biotechnology