  Using the measurements collected at a number of known locations by a moving
binary sensor, characterised by an unknown threshold, the problem is to
estimate the parameters of a biochemical source, continuously releasing
material into the atmosphere. The solution is formulated in the Bayesian
framework using a dispersion model of Poisson distributed particle encounters
in a turbulent flow. The method is implemented using the importance sampling
technique and successfully validated with three experimental datasets under
different wind conditions.
