Comparison of Three Methods for Estimating GPS Multipath Repeat Time

Wang, Minghua; Wang, Jiexian; Dong, Danan; Li, Haojun; Han, Litao; Chen, Wen

doi:10.3390/rs10020006

Cited by 32 publications

(20 citation statements)

References 18 publications

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“…There are three commonly used methods for estimating the repeat time: orbit repeat time method (ORTM) [25], aspect repeat time adjustment (ARTA) [24] and residual correlation method (RCM) [8]. The different mechanisms and algorithms of the three can be found in [26]. Without loss of generality, in this work, we adopt RCM.…”

Section: Resultsmentioning

confidence: 99%

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Tikhonov Regularization Based Modeling and Sidereal Filtering Mitigation of GNSS Multipath Errors

et al. 2018

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In Global Navigation Satellite System (GNSS) relative positioning applications, multipath errors are non-negligible. Mitigation of the multipath error is an important task for precise positioning and it is possible due to the repeatability, even without any rigorous mathematical model. Empirical modeling is required for this mitigation. In this work, the multipath error modeling using carrier phase measurement residuals is realized by solving a regularization problem. Two Tikhonov regularization schemes, namely with the first and the second order differences, are considered. For each scheme, efficient numerical algorithms are developed to find the solutions, namely the Thomas algorithm and Cholesky rank-one update algorithm for the first and the second differences, respectively. Regularization parameters or Lagrange multipliers are optimized using the bootstrap method. In experiment, data on the first day are processed to construct a multipath model for each satellite (except the reference one), and then the model is used to correct the measurement on the second day, namely following the sidereal filtering approach. The smoothness of the coordinates calculated using the corrected measurements is improved significantly compared to those using the raw measurement. The efficacy of the proposed method is illustrated by the actual calculation.

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Section: Resultsmentioning

confidence: 99%

“…For the latter case, the mitigation can be done in real time; and when time domain modeling is adopted, it is often called sidereal filtering [22]. In sidereal filtering, it is vital to determine the repeat time of the multipath errors [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Tikhonov Regularization Based Modeling and Sidereal Filtering Mitigation of GNSS Multipath Errors

et al. 2018

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“…This method is suitable for unmodeled system error handling [149,[155][156][157]. Taking the multipath effect as an example, it is still a challenge to develop a general multipath correction model for different GNSS stations [158]. EMD decomposes the time series into a series of intrinsic mode functions (IMFs) and a residual.…”

Section: Theorymentioning

confidence: 99%

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

et al. 2019

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In the past few decades, global navigation satellite system (GNSS) technology has been widely used in structural health monitoring (SHM), and the monitoring mode has evolved from long-term deformation monitoring to dynamic monitoring. This paper gives an overview of GNSS-based dynamic monitoring technologies for SHM. The review is classified into three parts, which include GNSS-based dynamic monitoring technologies for SHM, the improvement of GNSS-based dynamic monitoring technologies for SHM, as well as denoising and detrending algorithms. The significance and progress of Real-Time Kinematic (RTK), Precise Point Position (PPP), and direct displacement measurement techniques, as well as single-frequency technology for dynamic monitoring, are summarized, and the comparison of these technologies is given. The improvement of GNSS-based dynamic monitoring technologies for SHM is given from the perspective of multi-GNSS, a high-rate GNSS receiver, and the integration between the GNSS and accelerometer. In addition, the denoising and detrending algorithms for GNSS-based observations for SHM and corresponding applications are summarized. Challenges of low-cost and widely covered GNSS-based technologies for SHM are discussed, and problems are posed for future research.

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“…The third category method is based on the repetitive period of satellite constellation distribution in time domain, including sidereal filtering (SF) [19], modified sidereal filtering (MSF) [20][21][22][23] and Advanced Sidereal filtering (ASF) [24][25][26][27]. This type of method calculates the precise repeat periods of satellite orbits.…”

Section: Introductionmentioning

confidence: 99%

An Advanced Multipath Mitigation Method Based on Trend Surface Analysis

et al. 2020

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Among various ways to eliminate the multipath effect in high-precision global navigation satellite system positioning, the multipath hemispherical map (MHM) is a typical multipath correction method based on spatial domain repeatability, which is suitable for not only static environments, but also some dynamic carriers, such as ships and aircraft. So, it has notable advantages and is widely used. The MHM method divides the sky into grids according to the azimuth and elevation angles of satellite, and calculates the average of the residuals within the grid points as its multipath calibration value. It is easy to implement, but it will inevitably lead to excessive or insufficient multipath correction in the grid. The trend surface analysis-based multipath hemispherical map (T-MHM) method makes up for this deficiency by performing trend surface analysis on the multipath spatial changes within the grid points. However, the effectiveness of T-MHM is limited and less capable of resisting noise interference due to the multicollinearity between the independent variables caused by the special spatial distribution of multipath sampling and the overfitting problem caused by ignoring the multipath anisotropy. Thus, we proposed an improved multipath elimination method named AT-MHM (advanced trend surface analysis-based multipath hemispherical model), which cautiously judges the occurrence of the above problems and gives corresponding solutions. This was extended to double-difference mode, which expands the scope of application. The performance of AT-MHM in GPS pseudorange multipath mitigation was verified on geodetic receiver and low-cost receiver in a strong multipath environment with high occlusion.

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Comparison of Three Methods for Estimating GPS Multipath Repeat Time

Cited by 32 publications

References 18 publications

Tikhonov Regularization Based Modeling and Sidereal Filtering Mitigation of GNSS Multipath Errors

Tikhonov Regularization Based Modeling and Sidereal Filtering Mitigation of GNSS Multipath Errors

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

An Advanced Multipath Mitigation Method Based on Trend Surface Analysis

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