GLONASS–only FDMA+CDMA RTK: Performance and outlook

Zaminpardaz, Safoora; Teunissen, Peter; Khodabandeh, Amir

doi:10.1007/s10291-021-01132-z

Cited by 20 publications

(6 citation statements)

References 17 publications

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“…Teunissen [108] addressed this problem and proposed a new integer-estimable FDMA model that ensures the integer nature of FDMA ambiguities and guarantees a high success rate with partial integer ambiguity resolution. Many studies then applied this integer-estimable FDMA model to RTK and achieved great positioning performances [109][110][111][112]. Based on the integer-estimable FDMA model, Zhang et al [113] proposed an FDMA PPP-RTK solution and achieved fast FDMA integer ambiguity resolution in both homogeneous and heterogeneous networks.…”

Section: Frequency Division Multiple Access (Fdma) Ppp-rtkmentioning

confidence: 99%

Recent advances and perspectives in GNSS PPP-RTK

Hou¹,

Zha²,

Li³

et al. 2023

Meas. Sci. Technol.

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PPP-RTK, otherwise known as integer ambiguity resolution-enabled precise pointing positioning, has attracted much attention in recent years and has become state-of-the-art in the global navigation satellite system (GNSS) high-precision positioning community. This work reviews several PPP-RTK methods, outlines a set of PPP-RTK applications, and presents possible future developments. According to the parameterization considered, we clarify the PPP-RTK models into a distinct-clock category and two common-clock categories (common-clock-1 and common-clock-2), in which several ionosphere-free PPP-RTK models can be cast. Compared with the ionosphere-free PPP-RTK model, we emphasize the advantages of the undifferenced and uncombined (UDUC) formulation and recommend the common-clock-1 UDUC PPP-RTK model since it is optimal, flexible, and widely applicable. Based on what kinds of parameters can be estimated by PPP-RTK models, we outline the PPP-RTK applications in several aspects, including position-based applications, time transfer, atmospheric retrieval, and GNSS bias estimation. Despite the huge advances in GNSS PPP-RTK, future research should improve PPP-RTK performances in harsh environments and apply PPP-RTK to mass markets.

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Section: Frequency Division Multiple Access (Fdma) Ppp-rtkmentioning

confidence: 99%

Recent advances and perspectives in GNSS PPP-RTK

Hou¹,

Zha²,

Li³

et al. 2023

Meas. Sci. Technol.

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“…The most well-known of these is LAMBDA [ 51 , 52 ], which includes a reduction stage where the search space of ambiguities is reduced via decorrelation, followed by one of the `smart search’ algorithms to pick candidate ambiguity sets using the integer least-squares (ILS) criterion [ 53 ]. However, due to the presence of the matrix L , significant values of conditional variances of ambiguities for

and

for the FDMA model are produced [ 54 , 55 ]. As a result, Partial Ambiguity Resolution (PAR) should be used.…”

Section: Functional Modelmentioning

confidence: 99%

Multi-GNSS-Weighted Interpolated Tropospheric Delay to Improve Long-Baseline RTK Positioning

Mirmohammadian

Asgari

Verhagen

et al. 2022

Sensors

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Until now, RTK (real-time kinematic) and NRTK (Network-based RTK) have been the most popular cm-level accurate positioning approaches based on Global Navigation Satellite System (GNSS) signals in real-time. The tropospheric delay is a major source of RTK errors, especially for medium and long baselines. This source of error is difficult to quantify due to its reliance on highly variable atmospheric humidity. In this paper, we use the NRTK approach to estimate double-differenced zenith tropospheric delays alongside ambiguities and positions based on a complete set of multi-GNSS data in a sample 6-station network in Europe. The ZTD files published by IGS were used to validate the estimated ZTDs. The results confirmed a good agreement, with an average Root Mean Squares Error (RMSE) of about 12 mm. Although multiplying the unknowns makes the mathematical model less reliable in correctly fixing integer ambiguities, adding a priori interpolated ZTD as quasi-observations can improve positioning accuracy and Integer Ambiguity Resolution (IAR) performance. In this work, weighted least-squares (WLS) were performed using the interpolation of ZTD values of near reference stations of the IGS network. When using a well-known Kriging interpolation, the weights depend on the semivariogram, and a higher network density is required to obtain the correct covariance function. Hence, we used a simple interpolation strategy, which minimized the impact of altitude variability within the network. Compared to standard RTK where ZTD is assumed to be unknown, this technique improves the positioning accuracy by about 50%. It also increased the success rate for IAR by nearly 1.

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“…Therefore, different types of multi-GNSS observations can be combined, and existing integer ambiguity resolution methods can be directly applied. However, large values of the LAMBDA-decorrelated ambiguity conditional standard deviations for i = 2m − 2, i = 2m − 3 for the FDMA model is obtained due to the presence of the matrix L [38,39]. As a result, partial ambiguity resolution (PAR) should be used by letting the least precise transformed ambiguities float.…”

Section: Functional Modelmentioning

confidence: 99%

Improvement of Multi-GNSS Precision and Success Rate Using Realistic Stochastic Model of Observations

et al. 2021

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With the advancement of multi-constellation and multi-frequency global navigation satellite systems (GNSSs), more observations are available for high precision positioning applications. Although there is a lot of progress in the GNSS world, achieving realistic precision of the solution (neither too optimistic nor too pessimistic) is still an open problem. Weighting among different GNSS systems requires a realistic stochastic model for all observations to achieve the best linear unbiased estimation (BLUE) of unknown parameters in multi-GNSS data processing mode. In addition, the correct integer ambiguity resolution (IAR) becomes crucial in shortening the Time-To-Fix (TTF) in RTK, especially in challenging environmental conditions. In general, it is required to estimate various variances for observation types, consider the correlation between different observables, and compensate for the satellite elevation dependence of the observable precision. Quality control of GNSS signals, such as GPS, GLONASS, Galileo, and BeiDou can be performed by processing a zero or short baseline double difference pseudorange and carrier phase observations using the least-squares variance component estimation (LS-VCE). The efficacy of this method is investigated using real multi-GNSS data sets collected by the Trimble NETR9, SEPT POLARX5, and LEICA GR30 receivers. The results show that the standard deviation of observations depends on the system and the observable type in which a particular receiver could have the best performance. We also note that the estimated variances and correlations among different observations are also dependent on the receiver type. It is because the approaches utilized for the recovery techniques differ from one type of receiver to another kind. The reliability of IAR will improve if a realistic stochastic model is applied in single or multi-GNSS data processing. According to the results, for the data sets considered, a realistic stochastic model can increase the computed empirical success rate to 100% in multi-GNSS as well as a single system. As mentioned previously, the realistic precision of the solution can be achieved with a realistic stochastic model. However, using the estimated stochastic model, in fact, leads to better precision and accuracy for the estimated baseline components, up to 39% in multi-GNSS.

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GLONASS–only FDMA+CDMA RTK: Performance and outlook

Cited by 20 publications

References 17 publications

Recent advances and perspectives in GNSS PPP-RTK

Recent advances and perspectives in GNSS PPP-RTK

Multi-GNSS-Weighted Interpolated Tropospheric Delay to Improve Long-Baseline RTK Positioning

Improvement of Multi-GNSS Precision and Success Rate Using Realistic Stochastic Model of Observations

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