Localisation of an unknown number of land mines using a network of vapour detectors.
We consider the problem of localising an unknown number of land mines using concentration information provided by a wireless sensor network. A number of vapour sensors/detectors, deployed in the region of interest, are able to detect the concentration of the explosive vapours, emanating from buried land mines. The collected data is communicated to a fusion centre. Using a model for the transport of the explosive chemicals in the air, we determine the unknown number of sources using a Principal Component Analysis (PCA)-based technique. We also formulate the inverse problem of determining the positions and emission rates of the land mines using concentration measurements provided by the wireless sensor network. We present a solution for this problem based on a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme, and we compare it to the least squares optimisation approach. Experiments conducted on simulated data show the effectiveness of the proposed approach.
University of Technology of Compiègne, rue Roger Couttolenc, Compiègne 60200, France. hiba.hajchhade@hds.utc.fr.
Hiba Haj
HH
Chhadé
University of Technology of Compiègne, rue Roger Couttolenc, Compiègne 60200, France. fahed.abdallah@hds.utc.fr.
Fahed
F
Abdallah
Lebanese University, Beirut, Lebanon. imadmoug@ul.edu.lb.
Imad
I
Mougharbel
Department of Computer Science, University College London, WC1E 6BT London, UK. a.gning@cs.ucl.ac.uk.
Amadou
A
Gning
Department of Computer Science, University College London, WC1E 6BT London, UK. s.julier@cs.ucl.ac.uk.
Simon
S
Julier
University of Sheffield, S1 3JD Sheffield, UK. mila.mihaylova@ieee.org.
Lyudmila
L
Mihaylova