Statistical Trilateration with Skew-t Errors

Philipp Müller; Robert  Piche

doi:10.1109/ICL-GNSS.2015.7217164

Statistical Trilateration with Skew-t Errors

Philipp Müller, Robert Piche

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

166 Downloads (Pure)

Abstract

In the problem of determining a target's location using radio signal time-of-flight to reference nodes with known locations, measurement errors can be skewed because of multipath effects. In this paper, range errors are modelled using the skew-t distribution. An Expectation-Maximisation (EM) algorithm for computing the unknown location is presented, and its accuracy is compared with a descending Gauss-Newton algorithm by simulations. The EM algorithm improves the positioning accuracy significantly. Furthermore, it is shown how to fit the parameters of a skew-t distribution to training data using a Gibbs sampler.

Original language	English
Title of host publication	2015 International Conference on Localization and GNSS (ICL-GNSS)
Place of Publication	Gothenburg, Sweden
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Print)	9781479998593
DOIs	https://doi.org/10.1109/ICL-GNSS.2015.7217164
Publication status	Published - Jun 2015
Publication type	A4 Article in conference proceedings
Event	International Conference on Localization and GNSS - Duration: 1 Jan 1900 → …

Conference

Conference	International Conference on Localization and GNSS
Period	1/01/00 → …

Keywords

Statistical trilateration
skew-t distribution
Localization
Expectation Maximization
Gibbs sampler

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Publication forum level 1

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10.1109/ICL-GNSS.2015.7217164

Muller_and_Piche_Statistical_trilateration_with_skew-t_errors
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Accepted author manuscript, 189 KB

http://urn.fi/URN:NBN:fi:tty-201603013611

Cite this

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title = "Statistical Trilateration with Skew-t Errors",

abstract = "In the problem of determining a target's location using radio signal time-of-flight to reference nodes with known locations, measurement errors can be skewed because of multipath effects. In this paper, range errors are modelled using the skew-t distribution. An Expectation-Maximisation (EM) algorithm for computing the unknown location is presented, and its accuracy is compared with a descending Gauss-Newton algorithm by simulations. The EM algorithm improves the positioning accuracy significantly. Furthermore, it is shown how to fit the parameters of a skew-t distribution to training data using a Gibbs sampler.",

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AB - In the problem of determining a target's location using radio signal time-of-flight to reference nodes with known locations, measurement errors can be skewed because of multipath effects. In this paper, range errors are modelled using the skew-t distribution. An Expectation-Maximisation (EM) algorithm for computing the unknown location is presented, and its accuracy is compared with a descending Gauss-Newton algorithm by simulations. The EM algorithm improves the positioning accuracy significantly. Furthermore, it is shown how to fit the parameters of a skew-t distribution to training data using a Gibbs sampler.

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KW - skew-t distribution

KW - Localization

KW - Expectation Maximization

KW - Gibbs sampler

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BT - 2015 International Conference on Localization and GNSS (ICL-GNSS)

PB - IEEE

CY - Gothenburg, Sweden

T2 - International Conference on Localization and GNSS

Y2 - 1 January 1900

ER -

Statistical Trilateration with Skew-t Errors

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Keywords

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