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	<title>CACR Research Publications &#187; sensor density</title>
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		<title>An Analysis of Data Fusion For Radiation Detection and Localization</title>
		<link>http://www.cacr.caltech.edu/pubs/?p=460</link>
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		<pubDate>Mon, 29 Mar 2010 21:25:24 +0000</pubDate>
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				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[data fusion]]></category>
		<category><![CDATA[distributed sensor network]]></category>
		<category><![CDATA[Radiation detection]]></category>
		<category><![CDATA[sensor density]]></category>
		<category><![CDATA[surveillance]]></category>
		<category><![CDATA[threat identification]]></category>
		<category><![CDATA[threat localization]]></category>

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		<description><![CDATA[Submitted to the FUSION 2010, 13th International Conference on Information Fusion, 26-29 July 2010 EICC Edinburgh, UK
Annie H. Liu, Julian J. Bunn, K. Mani Chandy
This paper explores fundamental relations between critical parameters of distributed sensor networks (DSN) that detect and locate radiation sources. The paper presents mathematical analyses and Monte
Carlo methods that help understand fundamental [...]]]></description>
			<content:encoded><![CDATA[<p>Submitted to the FUSION 2010, 13th International Conference on Information Fusion, 26-29 July 2010 EICC Edinburgh, UK</p>
<p>Annie H. Liu, <strong>Julian J. Bunn</strong>, K. Mani Chandy</p>
<p>This paper explores fundamental relations between critical parameters of distributed sensor networks (DSN) that detect and locate radiation sources. The paper presents mathematical analyses and Monte<br />
Carlo methods that help understand fundamental trade-offs between the time to detect radiation sources, the probabilities of false positives and negatives, system cost, numbers of sensors, locations of sensors, mixes of sensors of different capabilities, benefits of data fusion, and communication load.</p>
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