Improving Localization Accuracy using Spatio-Temporal Information of Objects
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Authors
Rowe, Neil C.
Chen, Xiao
Singh, Gurminder
Subjects
Advisors
Date of Issue
2012-08
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Improvised explosive devices (IEDs) are an increasingly
serious military threat as is witnessed in Iraq and
Afghanistan. To combat the IED emplacement, it is important
to have persistent surveillance over time. Due to the low cost
and capabilities of sensors, wireless sensor networks (WSNs)
have tremendous potential for military and civilian surveillance.
In this paper, we explore methods to improve an important
aspect of surveillance: localization accuracy. Though there are
many localization algorithms in the literature, all of them try
to improve the accuracy from the side of sensor networks. In
this paper, we tackle this problem from a new angle, that is,
we look at the spatio-temporal relationships of objects we track,
which, as far as we know, unprecedented in this attempt. We first
develop algorithms that use spatial and temporal relationships
of objects separately and then design ones that combine them.
Experimental results show that all our proposed algorithms can
improve localization accuracy, especially those combined ones.
Moreover, since our methods use features related to objects
themselves and not the underlying localization mechanism, they
can be built on any localization algorithm to improve accuracy.
Type
Conference Paper
Description
Journal of Parallel and Distributed Computing, Vol. 72, Issue 8, August 2012
Series/Report No
Department
Computer Science (CS)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
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Format
Citation
Journal of Parallel and Distributed Computing, Vol. 72, Issue 8, August 2012
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.