Maximum Likelihood Localization of a Diffusive Point Source Using Binary Observations

In this paper, we investigate the problem of localization of a diffusive point source of gas based on binary observations provided by a distributed chemical sensor network. We motivate the use of the maximum likelihood (ML) estimator for this scenario by proving that it is consistent and asymptotica...

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Veröffentlicht in:	IEEE transactions on signal processing 2007-02, Vol.55 (2), p.665-676
Hauptverfasser:	Vijayakumaran, S., Levinbook, Y., Wong, T.F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Acoustic sensors Acoustic signal detection Applied sciences Asymptotic properties Chemical sensors Chemical technology Density Detection algorithms Detection, estimation, filtering, equalization, prediction Diffusion Diffusive source estimation theory Estimators Exact sciences and technology gas sensors Information, signal and communications theory Localization Maximum likelihood detection Maximum likelihood estimation Point sources Position (location) Sensor arrays Sensor phenomena and characterization Sensors Signal and communications theory Signal processing algorithms Signal, noise source localization Telecommunications and information theory
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