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Multi-platform Information-Based Sensor Management

By et al. Chris M. Kreuchner

Abstract

This paper shows how information-directed diffusion can be used to manage the trajectories of hundreds of smart mobile sensors. This is an artificial physics method in which the sensors move stochastically in response to an information gradient and artificial inter-sensor forces that serve to coordinate their actions. Measurements received by the sensors are centrally fused using a particle filter to estimate the Joint Multitarget Probability Density (JMPD) for the surveillance volume. The JMPD is used to construct an information surface which gives the expected gain for sensor dwells as a function of position. The updated sensor position is obtained by moving it in response to artificial forces derived from the information surface, which acts as a potential, and inter-sensor forces derived from a Lennard-Jones-like potential. The combination of information gradient and inter-sensor forces work to move the sensors to areas of high information gain while simultaneously ensuring sufficient spacing between the sensors. We evaluate the performance of this approach using a simulation study for an idealized Micro Air Vehicle with a simple EO detector and collected target trajectories. We find that this method provides a factor of 5 to 10 improvement in performance when compared to random uncoordinated search

Topics: sensor management, artificial physics, swarms
Year: 2005
DOI identifier: 10.1117/12.608436
OAI identifier: oai:CiteSeerX.psu:10.1.1.126.4270
Provided by: CiteSeerX
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