Received signal strength localization with an unknown path loss exponent

Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α ,...

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Published in2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE) pp. 000456 - 000459
Main Authors Chan, Y. T., Lee, B. H., Inkol, R., Chan, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
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ISBN9781424497881
1424497884
ISSN0840-7789
DOI10.1109/CCECE.2011.6030492

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Abstract Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α , where the path loss exponent, α, is typically between 2 and 4 depending on the terrain. This uncertainty is a problem since a solution for the emitter location obtained using a suboptimal choice of α will suffer from degraded accuracy. To resolve this issue, a near maximum likelihood (ML) estimator for both α and emitter position (x,y) has been developed. By expressing (x,y) in terms of α and substituting the results into the ML-function, the 3-D minimization problem is simplified to 1-D. A simple search in α then gives the (α,x,y) estimates. Simulation experiments corroborate the proposed approach and demonstrate estimation accuracy close to the Cramer-Rao Lower Bound.
AbstractList Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α , where the path loss exponent, α, is typically between 2 and 4 depending on the terrain. This uncertainty is a problem since a solution for the emitter location obtained using a suboptimal choice of α will suffer from degraded accuracy. To resolve this issue, a near maximum likelihood (ML) estimator for both α and emitter position (x,y) has been developed. By expressing (x,y) in terms of α and substituting the results into the ML-function, the 3-D minimization problem is simplified to 1-D. A simple search in α then gives the (α,x,y) estimates. Simulation experiments corroborate the proposed approach and demonstrate estimation accuracy close to the Cramer-Rao Lower Bound.
Author Chan, F.
Lee, B. H.
Inkol, R.
Chan, Y. T.
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  organization: Dept. of Electr. & Comput. Eng., R. Mil. Coll. of Canada, Kingston, ON, Canada
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Snippet Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable...
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StartPage 000456
SubjectTerms Cramer-Rao bounds
Fading
Geometry
Localization
Maximum likelihood estimation
received signal strength
Receivers
Simulation
Wireless sensor networks
Title Received signal strength localization with an unknown path loss exponent
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