Improving Real-Time Position Estimation Using Correlated Noise Models

Improving Real-Time Position Estimation Using Correlated Noise Models

We provide algorithms for inferring GPS (Global Positioning System) location and for quantifying the uncertainty of this estimate in real time. The algorithms are tested on GPS data from locations in the Southern Hemisphere at four significantly different latitudes. In order to rank the algorithms,...

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Bibliographic Details
Main Authors: Andrew Martin, Matthew Parry, Andy W. R. Soundy, Bradley J. Panckhurst, Phillip Brown, Timothy C. A. Molteno, Daniel Schumayer
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sensors
Subjects:
GPS
uncertainty quantification
sensor fusion
noise models
embedded computing
system performance evaluation
Online Access:https://www.mdpi.com/1424-8220/20/20/5913

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