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Tracking based plume detection.

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Call No.	Ph.D. 2007
Author	Nofsinger, Glenn T.
Title	Tracking based plume detection.
Date	2007
Abstract	The work in this thesis deals with a novel approach for detecting and tracking chemical plumes in distributed sensor networks. The ultimate objective is solving the inverse location problem: given unknown sources released at unknown times, the sensor network must estimate the location and number of sources. Traditional solutions to this problem suffer from the challenge of a large state space, and we therefore seek reduced dimensionality that would allow for real-time solutions. Existing methods are generally computationally intensive, and become intractable when applied to a large scale system that is capable of monitoring an entire city in real-time. This problem is approached by tracking plumes using methods similar to multiple target tracking (MTT) as opposed to purely physical model inverse solutions. Although this tracking approach requires a higher density of sensor nodes, larger numbers of simple binary low resolution sensors have the advantage of higher spatial resolution. Binary sensor observations are partitioned into tracks based a wind history derived likelihood. With the use of an estimator-based joint probability, groups of sensors form and rank hypotheses that explain the set of observations in the network.The main contribution of this work is track formation followed by the application of a custom estimator--this process is called the 2-step algorithm. We developed a customized estimator for plumes that allows the MTT-like algorithm to treat the plume tracking problem as the extreme instance of the multi-target tacking (MTT) problem. The central question: how can a MTT-like method be implemented for plumes in a network of simple sensors capable of only binary detection? The simulation experiments demonstrate that the tracking based approach outperforms uniform estimators in conditions of high wind direction variability.
Description	x, 132 leaves : ill. 28 cm.
Format	application/pdf
Advisor	George V. Cybenko
Subject	Multisensor data fusion. Sensor networks. Plumes (Fluid dynamics). Automatic tracking. Signal processing -- Digital techniques -- Mathematics.
College	Thayer School of Engineering.
Issuing Body	Dartmouth Dissertations are made available through the Dartmouth Digital Library.
Degree	Thesis (Ph.D.)--Dartmouth College.
Copyright	All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means without permission in writing from the author.
DOI	http://dx.doi.org/10.1349/ddlp.157

Title	Page 1
Format	application/pdf
Issuing Body	Dartmouth Dissertations are made available through the Dartmouth Digital Library.
Degree	Thesis (Ph.D.)--Dartmouth College.
Full Text	Tracking Based Plume Detection A Thesis Submitted to the Faculty in partial ful llment of the requirements for the degree of Doctor of Philosophy by Glenn T. Nofsinger DARTMOUTH COLLEGE Hanover, New Hampshire December 2006 Examining Committee: George V. Cybenko (chairman) Eric W. Hansen Vincent H. Berk Daniel Rockmore (Signature of Author) Charles K. Barlowe Dean of Graduate Students c 2006 Trustees of Dartmouth College

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Tracking based plume detection.

Tracking based plume detection.