Bayesian decision fusion, particle swarm optimization, multi objective optimization, sensor management
Electrical and Computer Engineering
This paper presents a Swarm Intelligence based approach for sensor management of a multi sensor networks. Alternate sensor configurations and fusion strategies are evaluated by swarm agents, and an optimum configuration and fusion strategy evolves. An evolutionary algorithm, particle swarm optimization, is modified to optimize two objectives: accuracy and time. The output of the algorithm is the choice of sensors, individual sensor's thresholds and the optimal decision fusion rule. The results achieved show the capability of the algorithm in selecting optimal configuration for a given requirement consisting of multiple objectives.
Veeramachaneni, Kalyan and Osadciw, Lisa Ann, "Dynamic Sensor Management Using Multi Objective Particle Swarm Optimizer" (2004). Electrical Engineering and Computer Science. Paper 125.