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Conference papers
Hybrid Navigation Filters Performances Between GPS, Galileo and 5G TOA Measurements in Multipath Environment
Abstract : In this paper, the performance of different hybrid navigation filters exploiting GPS, Galileo and 5G Time Of Arrival (TOA) measurements in multipath environment are studied. For the realism of the study, realistic propagation channels must be considered and their impacts on the received signals processing must be accurately modelled. GNSS signal mathematical models in multipath environment have been analyzed for a long time. However, 5G mathematical models in a realistic multipath environment are still in its early stages of analysis. This article is divided in three main parts. The first part is dedicated to the identification of compliant GNSS and 5G signal propagation channel models; SCHUN is selected for GNSS and QuaDRiGa is selected for 5G. Based on this, the correlator output mathematical models for 5G signals and GNSS signals are derived. The second part tackles the accurate characterization of the pseudo range errors due to propagation channels shadowing and multipath effect as well as thermal noise. This step is required for the correct derivation of the navigation filters. Indeed, the study will focus on Extended Kalman Filters (EKF) and Unscented Kalman Filters (UKF); both assume a Gaussian distribution of the errors. Therefore, by optimally characterizing the errors, the performances of the filters are expected to be improved. The last part consists in validating through simulations the theory and mathematical models developed in the first and second parts.
https://hal-enac.archives-ouvertes.fr/hal-02963979
Contributor : Laurence Porte Connect in order to contact the contributor
Submitted on : Monday, November 30, 2020 - 10:14:44 AM
Last modification on : Tuesday, October 19, 2021 - 11:02:55 AM
Long-term archiving on: : Monday, March 1, 2021 - 6:13:05 PM
Contributor : Laurence Porte Connect in order to contact the contributor
Submitted on : Monday, November 30, 2020 - 10:14:44 AM
Last modification on : Tuesday, October 19, 2021 - 11:02:55 AM
Long-term archiving on: : Monday, March 1, 2021 - 6:13:05 PM