Chemical source localization fusing concentration information in the presence of chemical background noise

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2017Author
Pomareda, Víctor
Magrans, Rudys
Jiménez Soto, Juan M.
Burgués, Javier
Marco, Santiago
Suggested citation
Pomareda, Víctor;
Magrans, Rudys;
Jiménez Soto, Juan M.;
Martínez Lacasa, Daniel;
Tresánchez Ribes, Marcel;
Burgués, Javier;
...
Marco, Santiago.
(2017)
.
Chemical source localization fusing concentration information in the presence of chemical background noise.
Sensors, 2017, vol. 17, núm. 904, p. 1-23.
https://doi.org/10.3390/s17040904.
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Show full item recordAbstract
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 experiments are used for evaluation purposes. For the simulations, we have
supposed that sensors are mounted on cars which do not have among its main tasks navigating
toward the source. To collect the real dataset, a special arena with induced wind is built, and an
autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for
sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better
estimation of the source location even for a low background level that benefits the performance of
binary version. The improvement is clear for the synthetic data while for real data the estimation
is only slightly better, probably because our exploration arena is not able to provide uniform wind
conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.
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Sensors, 2017, vol. 17, núm. 904, p. 1-23European research projects
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