Paper
1 April 2003 Sensor management: coverage versus survivability - a multiple-objective optimization problem
GeeWah Ng, Khin Hua Ng, Ee Lan Chia
Author Affiliations +
Abstract
The Sensor Management Team from DSO National Laboratories has developed a Decision Support System (DSS) to assist human operators in determining the most effective employment and/or deployment of a suite of sensors given a particular mission or operational scenario. The key issue addressed by the system is the resource allocation problem accompanied by two contradictory objectives, namely to maximize combined coverage of the sensor suite and to maximize survivability of the sensor within the suite. Furthermore, the system is to handle operational constraints on the usage of the suite of sensors. In this paper, we will describe how we handle the problem by formulating it as a Multiple Objective Optimization (MOO) problem. This system may be used as a pre-mission planning tool or a real time decision aid for the sensor suite commander. With the increase in size of the sensor suite and the number of possible deployment sites, the feasibility space of the employment/deployment configurations will grow tremendously. In order to allow for near real time decision support, the team has incorporated genetic algorithm to solve the MOO problem.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
GeeWah Ng, Khin Hua Ng, and Ee Lan Chia "Sensor management: coverage versus survivability - a multiple-objective optimization problem", Proc. SPIE 5099, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2003, (1 April 2003); https://doi.org/10.1117/12.486719
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Genetic algorithms

Radar

Decision support systems

Chemical elements

Field emission displays

Sensor networks

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