Chemical Source Localization Fusing Concentration Information in the Presence of Chemical Background Noise.

ABSTRACT: We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experime

SUBMITTER: Pomareda V 

PROVIDER: S-EPMC5426828 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature