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Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Medina, Daniel and Li, Haoqing and Vilà-Valls, Jordi and Closas, Pau (2021) Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments. Sensors, 21 (4). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/s21041250. ISSN 1424-8220.

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Official URL: https://www.mdpi.com/1424-8220/21/4/1250


Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

Item URL in elib:https://elib.dlr.de/142615/
Document Type:Article
Title:Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Medina, DanielUNSPECIFIEDhttps://orcid.org/0000-0002-1586-3269UNSPECIFIED
Li, HaoqingNortheastern UniversityUNSPECIFIEDUNSPECIFIED
Vilà-Valls, JordiUNSPECIFIEDhttps://orcid.org/0000-0001-7858-4171UNSPECIFIED
Closas, PauUNSPECIFIEDhttps://orcid.org/0000-0002-5960-6600UNSPECIFIED
Date:10 February 2021
Journal or Publication Title:Sensors
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:GNSS; Precise Positioning; Multipath; Kalman Filtering; Robust Filtering;
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication, Navigation, Quantum Technology
DLR - Research area:Raumfahrt
DLR - Program:R KNQ - Communication, Navigation, Quantum Technology
DLR - Research theme (Project):R - Project Navigation 4.0
Location: Neustrelitz
Institutes and Institutions:Institute of Communication and Navigation > Nautical Systems
Deposited By: Medina, Daniel
Deposited On:09 Jun 2021 16:50
Last Modified:24 May 2022 23:47

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