Role of the RLS-VCE-estimated stochastic model for improvement of accuracy and convergence time in multi-GNSS precise point positioning

Parvazi, Kamal; Farzaneh, Saeed; Safari, Abdolreza

doi:10.1016/j.measurement.2020.108073

Cited by 21 publications

(8 citation statements)

References 51 publications

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“…Researchers have proposed many stochastic models for estimating receiver noise standard deviation. Those stochastic models are generally a function of satellite elevation angle or Signal to Noise Ratio (SNR) (Parvazi et al, 2020). Among them, the sine stochastic function model based on satellite elevation angle is widely used (Parvazi et al, 2020) where σ 0 is the nominal value of measurement noise standard deviation.…”

Section: Empirical Stochastic Modelmentioning

confidence: 99%

“…In order to determine the weights of observations, researchers have proposed a variety of empirical stochastic models, which are usually a function of the satellite elevation angle, signal-to-noise ratio, carrier-to-noise ratio, or multipath factor, to estimate the measurement variance (Parvazi et al, 2020;Zhang et al, 2019aZhang et al, , 2019b. The coefficients of an empirical stochastic model are usually fixed.…”

Section: Introductionmentioning

confidence: 99%

“…This method can obtain the optimal state estimation theoretically, but needs to set many parallel filters, which will lead to serious memory resource consumption and affect the real-time performance. The VCE methods include Helmert Variance Component Estimation (HVCE) (Gao et al, 2016), Minimum Norm Quadratic Unbiased Estimator (MINQUE) (Zhang et al, 2019a(Zhang et al, , 2019b, the Best Invariant Quadratic Unbiased Estimator (BIQUE) (Zhang et al, 2019a(Zhang et al, , 2019b, and the Least-square Variance Component Estimator (LS-VCE) (Parvazi et al, 2020). They generally use the residuals to estimate the (co)variance of observations, which requires a lot of redundant observations to obtain reliable (co) variances.…”

Section: Introductionmentioning

confidence: 99%

“…They generally use the residuals to estimate the (co)variance of observations, which requires a lot of redundant observations to obtain reliable (co) variances. Therefore, the VCE methods are mainly used for post-processing analysis or to determine the scale factors of different types or groups of observations (Parvazi et al, 2020;Zhang et al, 2019aZhang et al, , 2019b. The covariance matching methods include the Residual-based Adaptive Estimation (RAE) (Lee et al, 2020) and the Innovationbased Adaptive Estimation (IAE) (Liu et al, 2021), which calculate the measurement covariance matrix based on the numerical relationship between the measurement error and measurement residual or innovation, respectively.…”

Section: Introductionmentioning

confidence: 99%

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A resilient adjustment method to weigh pseudorange observation in precise point positioning

2022

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The accurate weighting of pseudorange observations is important to improve the convergence time and positioning quality of Precise Point Positioning (PPP). Currently, the weight of a pseudorange observation is mainly determined with empirical stochastic models. However, in a complex environment, due to the inability to adapt for the dynamic changes of the user environment, the empirical stochastic models usually cannot reflect the real error level of pseudorange observations. To address this problem, a resilient adjustment method to weigh pseudorange observations is proposed, which constructs the real-time estimation and inflation model for the variance of pseudorange multipath error and measurement noise to replace the empirical stochastic model to determine the weights of pseudorange observations. A set of static and dynamic Global Positioning System (GPS) test data are used to verify the effectiveness of the proposed method. The test results indicate that the proposed real-time estimation model can provide a better representation of the pseudorange accuracy, and the positioning performance of PPP using the real-time estimation model is better than that with the empirical stochastic model. Compared with the optimal empirical stochastic model, the positioning accuracy of PPP with the real-time estimation model is improved by at least 20%, and the convergence time is reduced by at least 50%.

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Section: Empirical Stochastic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A resilient adjustment method to weigh pseudorange observation in precise point positioning

2022

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“…Using the Recursive Least Square Estimation-Variance Components Estimation (RLS-VCE) method [56] to estimate the accuracy of observations and the correlations between them…”

Section: Observation Weightmentioning

confidence: 99%

A Least Squares Solution to Regionalize VTEC Estimates for Positioning Applications

Farzaneh

Forootan

2020

Remote Sensing

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A new approach is presented to improve the spatial and temporal resolution of the Vertical Total Electron Content (VTEC) estimates for regional positioning applications. The proposed technique utilises a priori information from the Global Ionosphere Maps (GIMs) of the Center for Orbit Determination in Europe (CODE), provided in terms of Spherical Harmonic (SH) coefficients of up to degree and order 15. Then, it updates the VTEC estimates using a new set of base-functions (with better resolution than SHs) while using the measurements of a regional GNSS network. To achieve the highest accuracy possible, our implementation is based on a transformation of the GIM/CODE VTECs to their equivalent coefficients in terms of (spherical) Slepian functions. These functions are band-limited and reflect the majority of signal energy inside an arbitrarily defined region, yet their orthogonal property is remained. Then, new dual-frequency GNSS measurements are introduced to a Least Squares (LS) updating step that modifies the Slepian VTEC coefficients within the region of interest. Numerical application of this study is demonstrated using a synthetic example and ground-based GPS data in South America. The results are also validated against the VTEC estimations derived from independent GPS stations (that are not used in the modelling), and the VTEC products of international centres. Our results indicate that, by using 62 GPS stations in South America, the ionospheric delay estimation can be considerably improved. For example, using the new VTEC estimates in a Precise Point Positioning (PPP) experiment improved the positioning accuracy compared to the usage of GIM/CODE and Klobuchar models. The reductions in the root mean squared of errors were ∼23% and 25% for a day with moderate solar activity while 26% and ∼35% for a day with high solar activity, respectively.

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An Adaptive Weighted Model Considering Multipath for Precise Point Positioning

Zhang

Chen

Zhao

2021

Lecture Notes in Electrical Engineering

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Role of the RLS-VCE-estimated stochastic model for improvement of accuracy and convergence time in multi-GNSS precise point positioning

Cited by 21 publications

References 51 publications

A resilient adjustment method to weigh pseudorange observation in precise point positioning

A resilient adjustment method to weigh pseudorange observation in precise point positioning

A Least Squares Solution to Regionalize VTEC Estimates for Positioning Applications

An Adaptive Weighted Model Considering Multipath for Precise Point Positioning

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