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Evaluating Process and Measurement Noise in Extended Kalman Filter for GNSS Position Accuracy

Ngoc Tan Truong 1 Ali Khenchaf 1 Fabrice Comblet 1
1 Lab-STICC_ENSTAB_MOM_PIM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Extended Kalman filter (EKF) is widely used in the dynamic systems under the assumption that the process and measurement noises are Gaussian distributed. It is well known that the covariance matrixes of process noise and measurement noise have a significant impact on the EKF's performance. To evaluate its impact on the estimation of user position, this paper proposes two models. The first model depends on the power spectral densities of speed noise, clock bias noise and frequency drift noise to estimate covariance matrix of process noise. The second model is an exponential model that depends on the satellite elevation angle to estimate covariance matrix of measurement noise.
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https://hal.archives-ouvertes.fr/hal-02434624
Contributor : Marie Briec <>
Submitted on : Friday, January 10, 2020 - 11:13:10 AM
Last modification on : Tuesday, April 13, 2021 - 5:42:02 PM

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  • HAL Id : hal-02434624, version 1

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Ngoc Tan Truong, Ali Khenchaf, Fabrice Comblet. Evaluating Process and Measurement Noise in Extended Kalman Filter for GNSS Position Accuracy. 13th European Conference on Antennas and Propagation, EuCAP 2019, Mar 2019, Krakow, Poland. pp.8739375. ⟨hal-02434624⟩

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