Abstract:
In this paper, we investigated the problem of estimating the location of an
instantaneous source of an arbitrary gas using a simple chemical sensor
network.
We constructed the maximum likelihood estimator for this problem based on
binary observations. We utilized two different approaches, ML estimation
based on all the observations (i.e., batch processing) and approximated ML
estimation using only new observations and the previous estimate (i.e., real
time processing) . I will discuss the derivation and performance of these
estimators and will present some numerical results.