GNSS real‐time instantaneous velocimetry based on moving‐window polynomial modelling

Zhang, Laihong; Chang, Guobin; Chen, Chao; Zhang, Siyu; Zhu, Ting

doi:10.1049/iet-rsn.2020.0035

Cited by 6 publications

(1 citation statement)

References 38 publications

(37 reference statements)

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“…On the other hand, Moore and Wang (2003) proposed an extended state model, adding speed and acceleration parameters on the basis of the traditional model. Zhang et al (2020) combined the extended dynamic model and sliding window algorithm to smooth TDCP, and through dynamic experiment showed the accuracy of the proposed method is better than nonlinear tracking differentiator. To improve the accuracy of speed measurement, Wang et al (2020) further studied the influence of satellite orbit errors on velocity and proposed a new ionosphere-free wide-lane observation based on the combination of carrier phase observations.…”

Section: Introductionmentioning

confidence: 99%

A Doppler enhanced TDCP algorithm based on terrain adaptive and robust Kalman filter using a stand-alone receiver

Shao

Yang

et al. 2022

J. Navigation

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Time-differenced carrier phase (TDCP) is a commonly used method of precise velocimetry, but when the receiver is in a dynamic or complex observation environment, the estimation accuracy is reduced. Doppler velocimetry aims at estimating instantaneous velocity, and the accuracy is restricted by the accuracy of measurement. However, in such unfavourable cases, the Doppler measurement is more reliable than the carrier phase measurement. This paper derives the relationship between Doppler observation and TDCP observation, then proposes a Doppler enhanced TDCP algorithm, for the purpose of improving the velocity estimation accuracy in dynamic and complex observation environments. In addition, considering the error caused by the constant speed state update model in the robust Kalman filter (RKF), this paper designs a terrain adaptive and robust Kalman filter (TARKF). After three experimental tests, the improved TDCP algorithm can significantly increase the speed measurement accuracy to sub-metre per second, and the accuracy can be further improved after using TARKF.

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Section: Introductionmentioning

confidence: 99%

A Doppler enhanced TDCP algorithm based on terrain adaptive and robust Kalman filter using a stand-alone receiver

Shao

Yang

et al. 2022

J. Navigation

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Performance enhancement of PPP/SINS tightly coupled navigation based on improved robust maximum correntropy kalman filtering

Zhang,

Lou,

Song

et al. 2024

Advances in Space Research

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SINS attitude algorithm based on moving-window overdetermined polynomial fitting of gyro outputs

Fang¹,

Chang²,

Bao³

et al. 2021

Meas. Sci. Technol.

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The attitude algorithm is the most important part of the whole strapdown inertial navigation processing. It calculates the attitude of certain parameterization by integrating the gyro outputs or measurements in a specifically tailored way according to the attitude kinematic differential equation. The measurements or some angular velocity models obtained by fitting these measurements are often assumed free of errors in order to assess the numerical errors only. However, the gyro outputs and hence the models from them are by no means free of measurement errors. It is more often than not that the measurement errors dominate the numerical ones in practice. In this study, with coping with the measurement errors as the focus, we aim to improve the angular velocity model which is used as input in an attitude integration algorithm. This is achieved by exploiting the potential of overdetermined least-squares polynomial fitting. In order to avoid reducing the update rate by incorporating more measurements, the moving window trick is employed to re-use measurements in the previous update interval. The conventional attitude algorithm with second-order approximation in solving the differential equation of the equivalent rotation vector is employed as an example; however, the proposed method can be readily applied to other parameterizations such as direction cosine matrix, quaternion or Rodrigues parameters, and other high order approximations in solving the differential equation widely studied recently.

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GNSS real‐time instantaneous velocimetry based on moving‐window polynomial modelling

Cited by 6 publications

References 38 publications

A Doppler enhanced TDCP algorithm based on terrain adaptive and robust Kalman filter using a stand-alone receiver

A Doppler enhanced TDCP algorithm based on terrain adaptive and robust Kalman filter using a stand-alone receiver

Performance enhancement of PPP/SINS tightly coupled navigation based on improved robust maximum correntropy kalman filtering

SINS attitude algorithm based on moving-window overdetermined polynomial fitting of gyro outputs

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