Paper
26 May 2005 Multi-platform information-based sensor management
Author Affiliations +
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chris M. Kreucher, Keith D. Kastella, and Alfred O. Hero III "Multi-platform information-based sensor management", Proc. SPIE 5820, Defense Transformation and Network-Centric Systems, (26 May 2005); https://doi.org/10.1117/12.608436
Lens.org Logo
CITATIONS
Cited by 16 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Motion models

Target detection

Physics

Surveillance

Signal to noise ratio

Kinematics

RELATED CONTENT


Back to Top