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Communication Dans Un Congrès Année : 2019

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

Ali Khenchaf
Fabrice Comblet

Résumé

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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Dates et versions

hal-02434624 , version 1 (10-01-2020)

Identifiants

  • HAL Id : hal-02434624 , version 1

Citer

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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