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Proceedings Paper

Optimal placement of multiple types of communicating sensors with availability and coverage redundancy constraints
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Paper Abstract

Determination of an optimal configuration (numbers, types, and locations) of a sensor network is an important practical problem. In most applications, complex signal propagation effects and inhomogeneous coverage preferences lead to an optimal solution that is highly irregular and nonintuitive. The general optimization problem can be strictly formulated as a binary linear programming problem. Due to the combinatorial nature of this problem, however, its strict solution requires significant computational resources (NP-complete class of complexity) and is unobtainable for large spatial grids of candidate sensor locations. For this reason, a greedy algorithm for approximate solution was recently introduced [S. N. Vecherin, D. K. Wilson, and C. L. Pettit, "Optimal sensor placement with terrain-based constraints and signal propagation effects," Unattended Ground, Sea, and Air Sensor Technologies and Applications XI, SPIE Proc. Vol. 7333, paper 73330S (2009)]. Here further extensions to the developed algorithm are presented to include such practical needs and constraints as sensor availability, coverage by multiple sensors, and wireless communication of the sensor information. Both communication and detection are considered in a probabilistic framework. Communication signal and signature propagation effects are taken into account when calculating probabilities of communication and detection. Comparison of approximate and strict solutions on reduced-size problems suggests that the approximate algorithm yields quick and good solutions, which thus justifies using that algorithm for full-size problems. Examples of three-dimensional outdoor sensor placement are provided using a terrain-based software analysis tool.

Paper Details

Date Published: 22 April 2010
PDF: 10 pages
Proc. SPIE 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR, 76940U (22 April 2010); doi: 10.1117/12.849327
Show Author Affiliations
Sergey N. Vecherin, U.S. Army Cold Regions Research and Engineering Lab. (United States)
New Mexico State Univ. (United States)
D. Keith Wilson, U.S. Army Cold Regions Research and Engineering Lab. (United States)
Chris L. Pettit, U.S. Naval Academy (United States)

Published in SPIE Proceedings Vol. 7694:
Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR
Michael A. Kolodny, Editor(s)

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