A key to mastering asymmetric warfare is the acquisition of accurate intelligence on adversaries and their assets in urban and open battlefields. To achieve this, one needs adequate numbers of tactical sensors placed in locations to optimize coverage, where optimality is realized by covering a given area of interest with the least number of sensors, or covering the largest possible subsection of an area of interest with a fixed set of sensors. Unfortunately, neither problem admits a polynomial time algorithm as a solution, and therefore, the placement of such sensors must utilize intelligent heuristics instead. In this paper, we present a scheme implemented on parallel SIMD processing architectures to yield significantly faster results, and that is highly scalable with respect to dynamic changes in the area of interest. Furthermore, the solution to the first problem immediately translates to serve as a solution to the latter if and when any sensors are rendered inoperable.

Date Published: 1 May 2008
PDF: 8 pages
Proc. SPIE 6961, Intelligent Computing: Theory and Applications VI, 69610H (1 May 2008); doi: 10.1117/12.780282

Published in SPIE Proceedings Vol. 6961:
Intelligent Computing: Theory and Applications VI
Kevin L. Priddy; Emre Ertin, Editor(s)