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Probabilistic Sensing Model for Sensor Placement Optimization based on Line-of-sight Coverage

Vahab Akbarzadeh, Christian Gagné, Marc Parizeau, Meysam Argany and Mir Abolfazl Mostafavi
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Abstract - This paper proposes a probabilistic sensor model for the optimization of sensor placement. Traditional schemes rely on simple sensor behaviours and environmental factors. The consequences of these oversimplications are unrealistic simulation of sensor performance and, thus, suboptimal sensor placement. In this paper, we develop a novel probabilistic sensing model for sensors with line-of-sight based coverage (e.g. cameras) to tackle the sensor placement problem for these sensors. The probabilistic sensing model consists of membership functions for sensing range and sensing angle, which takes into consideration sensing capacity probability as well as critical environmental factors such as terrain topography. We then implement several optimization schemes for sensor placement optimization, including simulated annealing, L-BFGS, and CMA-ES.

Bibtex:

@article{Akbarzadeh948,
author    = { Vahab Akbarzadeh and Christian Gagné and Marc Parizeau and Meysam Argany and Mir Abolfazl Mostafavi },
title     = { Probabilistic Sensing Model for Sensor Placement Optimization based on Line-of-sight Coverage },
volume    = { 62 },
number    = { 2 },
pages     = { 293--303 },
year      = { 2013 },
month     = { 2 },
journal   = { IEEE Transactions on Instrumentation and Measurement },
web       = { http://dx.doi.org/10.1109/TIM.2012.2214952 }
}

Dernière modification: 2012/11/01 par cgagne

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