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

Sensors

Hiba Haj Chhadé²  Fahed Abdallah²  Imad Mougharbel¹  Amadou Gning³  Simon Julier³ 

[1] Lebanese University, Beirut, Lebanon; E-Mail:;University of Technology of Compiègne, rue Roger Couttolenc, Compiègne 60200, France; E-Mail:;Department of Computer Science, University College London, WC1E 6BT London, UK; E-Mails:

关键词: land mines localisation;    advection-diffusion;    inverse problem;    Bayesian inference;    Markov chain Monte Carlo;    PCA;   

DOI  :  10.3390/s141121000

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.