Rigorous sensor resource management: Methodology and evolutionary optimization
Document Type
Conference Proceeding
Department or Administrative Unit
Computer Science
Publication Date
5-26-2015
Abstract
The number of platforms and sensors with the best capabilities often is limited in the stressing tasking environment relative to the sensing needs. This is the case for Overhead Persistent InfraRed (OPIR) sensors. Sensor assets differ significantly in number, location, and capability over time. Planning for engagements prior to actual tasking sensors involves these factors. This paper proposes a new sensor tasking methodology and optimization models for both long-time planning and real-time Sensor Resource Management (SRM). It is based on the rigorous and adaptive mathematical formulation of the problem and the use of Computational Intelligence techniques such as genetic algorithms and dynamic logic to find a solution.
Recommended Citation
Kovalerchuk, B., & Perlovsky, L. (2015). Rigorous sensor resource management: Methodology and evolutionary optimization. 2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA). https://doi.org/10.1109/cisda.2015.7208621
Journal
2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)
Rights
Copyright © 2015, IEEE
Comments
This article was originally published in 2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA). The full-text article from the publisher can be found here.
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