State and Measurement Noise in Positioning and Tracking: Covariance Matrices Estimation and Gaussianity Assessment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952490" target="_blank" >RIV/49777513:23520/18:43952490 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/PLANS.2018.8373523" target="_blank" >https://doi.org/10.1109/PLANS.2018.8373523</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/PLANS.2018.8373523" target="_blank" >10.1109/PLANS.2018.8373523</a>

Jazyk výsledku

angličtina

Název v původním jazyce

State and Measurement Noise in Positioning and Tracking: Covariance Matrices Estimation and Gaussianity Assessment

Popis výsledku v původním jazyce

The paper presents the Noise covariance matrices Estimation with Gaussianity Assessment (NEGA) method that describes the noise characteristics of a linear time-varying statespace model. In particular, the motivation is placed on the state covariance matrices noise estimates combined with assessment of whether measurements noises are Gaussian or not. The proposed NEGA method, which belongs into the group of the correlation methods, provides unbiased and consistent noise covariance matrices estimate and hypothesis testing based decisions regarding the noises Gaussianity. Simultaneously conducting estimate and assessment is essential for an optimal design of any reliable and integrity-assured positioning and tracking algorithm. The proposed method applicability is extended for the nonlinear systems and thoroughly illustrated in numerical examples of both a nonlinear tracking example and a global navigation satellite system (GNSS) based positioning.

Název v anglickém jazyce

State and Measurement Noise in Positioning and Tracking: Covariance Matrices Estimation and Gaussianity Assessment

Popis výsledku anglicky

The paper presents the Noise covariance matrices Estimation with Gaussianity Assessment (NEGA) method that describes the noise characteristics of a linear time-varying statespace model. In particular, the motivation is placed on the state covariance matrices noise estimates combined with assessment of whether measurements noises are Gaussian or not. The proposed NEGA method, which belongs into the group of the correlation methods, provides unbiased and consistent noise covariance matrices estimate and hypothesis testing based decisions regarding the noises Gaussianity. Simultaneously conducting estimate and assessment is essential for an optimal design of any reliable and integrity-assured positioning and tracking algorithm. The proposed method applicability is extended for the nonlinear systems and thoroughly illustrated in numerical examples of both a nonlinear tracking example and a global navigation satellite system (GNSS) based positioning.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GC16-19999J" target="_blank" >GC16-19999J: Kooperativní přístupy k návrhu nelineárních filtrů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)

ISBN

978-1-5386-1647-5

ISSN

2153-358X

e-ISSN

2153-3598

Počet stran výsledku

10

Strana od-do

1326-1335

Název nakladatele

IEEE

Místo vydání

Monterey, USA

Místo konání akce

Monterey, USA

Datum konání akce

23. 4. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000435257800168