Next Article in Journal
A Provably-Secure ECC-Based Authentication Scheme for Wireless Sensor Networks
Previous Article in Journal
Measuring Snow Liquid Water Content with Low-Cost GPS Receivers
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(11), 21000-21022; doi:10.3390/s141121000

Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

1
University of Technology of Compiègne, rue Roger Couttolenc, Compiègne 60200, France
2
Lebanese University, Beirut, Lebanon
3
Department of Computer Science, University College London, WC1E 6BT London, UK
4
University of Sheffield, S1 3JD Sheffield, UK
*
Author to whom correspondence should be addressed.
Received: 19 June 2014 / Revised: 15 October 2014 / Accepted: 21 October 2014 / Published: 6 November 2014
(This article belongs to the Section Chemical Sensors)
View Full-Text   |   Download PDF [457 KB, uploaded 17 November 2014]   |  

Abstract

We consider the problem of localising an unknown number of land mines usingconcentration information provided by a wireless sensor network. A number of vapoursensors/detectors, deployed in the region of interest, are able to detect the concentrationof the explosive vapours, emanating from buried land mines. The collected data iscommunicated to a fusion centre. Using a model for the transport of the explosive chemicalsin the air, we determine the unknown number of sources using a Principal ComponentAnalysis (PCA)-based technique. We also formulate the inverse problem of determiningthe positions and emission rates of the land mines using concentration measurementsprovided by the wireless sensor network. We present a solution for this problem basedon a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme,and we compare it to the least squares optimisation approach. Experiments conducted onsimulated data show the effectiveness of the proposed approach. View Full-Text
Keywords: land mines localisation; advection-diffusion; inverse problem; Bayesianinference; Markov chain Monte Carlo; PCA land mines localisation; advection-diffusion; inverse problem; Bayesianinference; Markov chain Monte Carlo; PCA
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chhadé, H.H.; Abdallah, F.; Mougharbel, I.; Gning, A.; Julier, S.; Mihaylova, L. Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors. Sensors 2014, 14, 21000-21022.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top