Biasing emitter location estimates via false location injection
We consider the problem of a rogue introducing bias into a network estimating location under the time difference of arrival (TDOA) method. In particular we consider how a rogue by injecting only a single false sensor position can drive the network's location estimate a specified distance away f...
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creator | Huie, L. M. Fowler, M. L. |
description | We consider the problem of a rogue introducing bias into a network estimating location under the time difference of arrival (TDOA) method. In particular we consider how a rogue by injecting only a single false sensor position can drive the network's location estimate a specified distance away from the true value. The least squares (LS) residuals is minimized to find the false location to inject given the rogue's desired distance offset. In order to illustrate the success of our method, we consider the statistical tools that the locating network might employ to handle our false information injection including least squares and in the presence of outliers robust least median squares (LMS). We show that our method can successfully bias the location estimate of an estimating network when both LS and LMS methods are used. |
doi_str_mv | 10.1109/SSP.2011.5967672 |
format | Conference Proceeding |
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M. ; Fowler, M. L.</creator><creatorcontrib>Huie, L. M. ; Fowler, M. L.</creatorcontrib><description>We consider the problem of a rogue introducing bias into a network estimating location under the time difference of arrival (TDOA) method. In particular we consider how a rogue by injecting only a single false sensor position can drive the network's location estimate a specified distance away from the true value. The least squares (LS) residuals is minimized to find the false location to inject given the rogue's desired distance offset. In order to illustrate the success of our method, we consider the statistical tools that the locating network might employ to handle our false information injection including least squares and in the presence of outliers robust least median squares (LMS). We show that our method can successfully bias the location estimate of an estimating network when both LS and LMS methods are used.</description><identifier>ISSN: 2373-0803</identifier><identifier>ISBN: 9781457705694</identifier><identifier>ISBN: 1457705699</identifier><identifier>EISSN: 2693-3551</identifier><identifier>EISBN: 1457705702</identifier><identifier>EISBN: 9781457705687</identifier><identifier>EISBN: 9781457705700</identifier><identifier>EISBN: 1457705680</identifier><identifier>DOI: 10.1109/SSP.2011.5967672</identifier><language>eng</language><publisher>IEEE</publisher><subject>Accuracy ; Emitter location ; Estimation ; information injection ; Jacobian matrices ; Least squares approximation ; non-linear least squares ; Robustness ; Signal to noise ratio ; TDOA ; Weight measurement</subject><ispartof>2011 IEEE Statistical Signal Processing Workshop (SSP), 2011, p.249-252</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5967672$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5967672$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Huie, L. M.</creatorcontrib><creatorcontrib>Fowler, M. L.</creatorcontrib><title>Biasing emitter location estimates via false location injection</title><title>2011 IEEE Statistical Signal Processing Workshop (SSP)</title><addtitle>SSP</addtitle><description>We consider the problem of a rogue introducing bias into a network estimating location under the time difference of arrival (TDOA) method. In particular we consider how a rogue by injecting only a single false sensor position can drive the network's location estimate a specified distance away from the true value. The least squares (LS) residuals is minimized to find the false location to inject given the rogue's desired distance offset. In order to illustrate the success of our method, we consider the statistical tools that the locating network might employ to handle our false information injection including least squares and in the presence of outliers robust least median squares (LMS). We show that our method can successfully bias the location estimate of an estimating network when both LS and LMS methods are used.</description><subject>Accuracy</subject><subject>Emitter location</subject><subject>Estimation</subject><subject>information injection</subject><subject>Jacobian matrices</subject><subject>Least squares approximation</subject><subject>non-linear least squares</subject><subject>Robustness</subject><subject>Signal to noise ratio</subject><subject>TDOA</subject><subject>Weight measurement</subject><issn>2373-0803</issn><issn>2693-3551</issn><isbn>9781457705694</isbn><isbn>1457705699</isbn><isbn>1457705702</isbn><isbn>9781457705687</isbn><isbn>9781457705700</isbn><isbn>1457705680</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkEtLxDAUheMLHMfuBTf9A603SZObrEQHXzCgMLoe0uRWMsx0pAmC_96qBVffgQ8Oh8PYBYeac7BXq9VLLYDzWlmNGsUBO-ONQgSFIA7ZTGgrK6kUP2KFRTM5bZvj0UmUFRiQp6xIaQMAXBshjZix69voUuzfS9rFnGkot3vvctz3JaUcdy5TKj-jKzu3TfQvY78h_5PO2cmvKibO2dv93evisVo-PzwtbpZV5KhypU0rMXj0DRD5lltsyEoVRjbSO0SHzqkWQudQBOU7bgNZDEY7cMFLOWeXf72RiNYfwzht-FpPX8hv7mFPAg</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Huie, L. M.</creator><creator>Fowler, M. L.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201106</creationdate><title>Biasing emitter location estimates via false location injection</title><author>Huie, L. M. ; Fowler, M. L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-68b37dc7c40eecb1974e935d97443ca77a7aa5b0dfa72d5cf19de97d86a0adc33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Accuracy</topic><topic>Emitter location</topic><topic>Estimation</topic><topic>information injection</topic><topic>Jacobian matrices</topic><topic>Least squares approximation</topic><topic>non-linear least squares</topic><topic>Robustness</topic><topic>Signal to noise ratio</topic><topic>TDOA</topic><topic>Weight measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Huie, L. M.</creatorcontrib><creatorcontrib>Fowler, M. L.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Huie, L. M.</au><au>Fowler, M. L.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Biasing emitter location estimates via false location injection</atitle><btitle>2011 IEEE Statistical Signal Processing Workshop (SSP)</btitle><stitle>SSP</stitle><date>2011-06</date><risdate>2011</risdate><spage>249</spage><epage>252</epage><pages>249-252</pages><issn>2373-0803</issn><eissn>2693-3551</eissn><isbn>9781457705694</isbn><isbn>1457705699</isbn><eisbn>1457705702</eisbn><eisbn>9781457705687</eisbn><eisbn>9781457705700</eisbn><eisbn>1457705680</eisbn><abstract>We consider the problem of a rogue introducing bias into a network estimating location under the time difference of arrival (TDOA) method. In particular we consider how a rogue by injecting only a single false sensor position can drive the network's location estimate a specified distance away from the true value. The least squares (LS) residuals is minimized to find the false location to inject given the rogue's desired distance offset. In order to illustrate the success of our method, we consider the statistical tools that the locating network might employ to handle our false information injection including least squares and in the presence of outliers robust least median squares (LMS). We show that our method can successfully bias the location estimate of an estimating network when both LS and LMS methods are used.</abstract><pub>IEEE</pub><doi>10.1109/SSP.2011.5967672</doi><tpages>4</tpages></addata></record> |
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subjects | Accuracy Emitter location Estimation information injection Jacobian matrices Least squares approximation non-linear least squares Robustness Signal to noise ratio TDOA Weight measurement |
title | Biasing emitter location estimates via false location injection |
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