Multiple land mines localization using a wireless sensor network

This paper considers the problem of localization of multiple land mines using information collected by a network of wireless sensors deployed in the area of interest. These sensors detect the concentration of explosive vapours, emanating from buried land mines, in the air and have a wireless transmission system for exchanging information with a treatment or fusion centre. One of the key contribution of this paper is to locate and estimate the emission rate of multiple land mines. Using a model for the transport of the explosive chemicals in the air, we formulate the inverse problem consisting in determining sequentially the positions and emission rates of the land mines knowing concentration measurements provided by the sensors. To solve the inverse problem, we present a first solution based on a Least Squares optimization approach and a second solution based on probabilistic Bayesian techniques using a Markov Chain Monte Carlo sampling scheme. These two approaches are tested and compared on simulated data.