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Over the past two decades, low-cost single-frequency Global Navigation Satellite System (GNSS) receivers have been used in numerous engineering fields and applications due to their affordability and practicality. However, their main drawback has been the inability to track satellite signals in multiple frequencies, limiting their usage to short baselines only. In recent years, low-cost dual-frequency GNSS receivers equipped with Real-Time-Kinematic (RTK) engines entered the mass market, addressing many of the limitations of single-frequency GNSS receivers. This review article aimed to analyze the observations and positioning quality of low-cost GNSS receivers in different positioning methods. To provide answers to defined research questions, relevant studies on the topic were selected and investigated. From the analyzed studies, it was found that GNSS observations obtained from low-cost GNSS receivers have lower quality compared to geodetic counterparts, however, they can still provide positioning solutions with comparable accuracy in static and kinematic positioning modes, particularly for short baselines. Challenges persist in achieving high positioning accuracy over longer baselines and in adverse conditions, even with dual-frequency GNSS receivers. In the upcoming years, low-cost GNSS technology is expected to become increasingly accessible and widely utilized, effectively meeting the growing demand for positioning and navigation. [ABSTRACT FROM AUTHOR]

Dense Global Navigation Satellite System (GNSS) observations are beneficial for monitoring the small-scale troposphere turbulence in both spatiotemporal domains. Densification of current geodetic GNSS networks can be achieved by incorporating low-cost GNSS receivers and antennas, benefitting weather monitoring. This study aims to focus on real-time tropospheric delay estimation using real-time GNSS data streams collected by low-cost GNSS receivers and antennas. The results indicate that: (1) Low-cost GNSS devices can offer accuracies of 7.5 mm in winter and 10.8 mm in summer for real-time zenith tropospheric delay (ZTD) estimations; (2) By applying the phase center variation corrections for low-cost GNSS antennas, which are often ignored in previous studies on low-cost GNSS applications, can produce more reliable real-time ZTD estimations; (3) Low-cost GNSS devices can capture the ZTD fluctuations under heavy precipitation events in a real-time mode, showing a great potential as sensors to monitoring severe weather. These results underscore the viability of low-cost GNSS devices as cost-effective sensors that complement geodetic GNSS equipment in real-time troposphere monitoring and forecasting, especially at small scales. Their integration aids in the densification of existing monitoring networks, thereby bolstering GNSS meteorology applications. [ABSTRACT FROM AUTHOR]

Abstract The integer least squares (ILS) estimation is commonly used for carrier phase ambiguity resolution (AR). More recently, the best integer equivariant (BIE) estimation has also attracted an attention for complex application scenarios, which exhibits higher reliability by a weighted fusion of integer candidates. However, traditional BIE estimation with Gaussian distribution (GBIE) faces challenges in fully utilizing the advantages of BIE for urban low-cost positioning, mainly due to the presence of outliers and unmodeled errors. To this end, an improved BIE estimation method with Laplacian distribution (LBIE) is proposed, and several key issues are discussed, including the weight function of LBIE, determination of the candidates included based on the OIA test, and derivation of the variance of LBIE solutions for reliability evaluation. The results show that the proposed LBIE method has the positioning accuracy similar to the BIE using multivariate t-distribution (TBIE), and significantly outperforms the ILS-PAR and GBIE methods. In an urban expressway test with a Huawei Mate40 smartphone, the LBIE method has positioning errors of less than 0.5 m in three directions and obtains over 50% improvements compared to the ILS-PAR and GBIE methods. In an urban canyon test with a low-cost receiver STA8100 produced by STMicroelectronics, the positioning accuracy of LBIE in three directions is 0.112 m, 0.107 m, and 0.252 m, respectively, with improvements of 17.6%, 27.2%, and 26.1% compared to GBIE, and 23.3%, 28.2%, and 30.6% compared to ILS-PAR. Moreover, its computational time increases by 30–40% compared to ILS-PAR and is approximately half of that using TBIE.

The integer least squares (ILS) estimation is commonly used for carrier phase ambiguity resolution (AR). More recently, the best integer equivariant (BIE) estimation has also attracted an attention for complex application scenarios, which exhibits higher reliability by a weighted fusion of integer candidates. However, traditional BIE estimation with Gaussian distribution (GBIE) faces challenges in fully utilizing the advantages of BIE for urban low-cost positioning, mainly due to the presence of outliers and unmodeled errors. To this end, an improved BIE estimation method with Laplacian distribution (LBIE) is proposed, and several key issues are discussed, including the weight function of LBIE, determination of the candidates included based on the OIA test, and derivation of the variance of LBIE solutions for reliability evaluation. The results show that the proposed LBIE method has the positioning accuracy similar to the BIE using multivariate t-distribution (TBIE), and significantly outperforms the ILS-PAR and GBIE methods. In an urban expressway test with a Huawei Mate40 smartphone, the LBIE method has positioning errors of less than 0.5 m in three directions and obtains over 50% improvements compared to the ILS-PAR and GBIE methods. In an urban canyon test with a low-cost receiver STA8100 produced by STMicroelectronics, the positioning accuracy of LBIE in three directions is 0.112 m, 0.107 m, and 0.252 m, respectively, with improvements of 17.6%, 27.2%, and 26.1% compared to GBIE, and 23.3%, 28.2%, and 30.6% compared to ILS-PAR. Moreover, its computational time increases by 30–40% compared to ILS-PAR and is approximately half of that using TBIE. [ABSTRACT FROM AUTHOR]

The decrease in costs and dimensions of GNSS receivers has enabled their adoption for a very wide range of users. Formerly mediocre positioning performance is benefiting from recent technology advances, namely the adoption of multi-constellation, multi-frequency receivers. In our study, we evaluate signal characteristics and horizontal accuracies achievable with two low-cost receivers—a Google Pixel 5 smartphone and a u-Blox ZED F9P standalone receiver. The considered conditions include open area with nearly optimal signal reception, but also locations with differing amounts of tree canopy. GNSS data were acquired using ten 20 min observations under leaf-on and leaf-off conditions. Post-processing in static mode was conducted using the Demo5 fork of the RTKLIB open source software, which is adapted for usage with lower quality measurement data. The F9P receiver provided consistent results with sub-decimeter median horizontal errors even under tree canopy. The errors for the Pixel 5 smartphone were under 0.5 m under open-sky conditions and around 1.5 m under vegetation canopy. The adaptation of the post-processing software to lower quality data was proven crucial, especially for the smartphone. In terms of signal quality (carrier-to-noise density, multipath), the standalone receiver provided significantly better data than the smartphone. [ABSTRACT FROM AUTHOR]

Water vapour is a highly variable constituent of the troposphere; thus, its high-resolution measurements are of great importance to weather prediction systems. The Global Navigation Satellite Systems (GNSS) are operationally used in the estimation of the tropospheric state and assimilation of the results into the weather models. One of the GNSS techniques of troposphere sensing is tomography which provides 3-D fields of wet refractivity. The tomographic results have been successfully assimilated into the numerical weather models, showing the great potential of this technique. The GNSS tomography can be based on two different approaches to the parameterisation of the model’s domain, i.e. block (voxel-based) or grid (node-based) approach. Regardless of the parameterisation approach, the tomographic domain should be discretised, which is usually performed in a regular manner, with a grid resolution depending on the mean distance between the GNSS receivers. In this work, we propose a new parameterisation approach based on the optimisation of the tomographic nodes’ location, taking into account the non-uniform distribution of the GNSS information in the troposphere. The experiment was performed using a dense network of 16 low-cost multi-GNSS receivers located in Wrocław and its suburbs, with a mean distance of 3 km. Cross-validation of four different parameterisation approaches is presented. The validation is performed based on the Weather Research and Forecasting model as well as radiosonde observations. The new approach improves the results of wet refractivity estimation by 0.5–2 ppm in terms of RMSE, especially for altitudes of 0.5–2.0 km. [ABSTRACT FROM AUTHOR]

The recent advances of low-cost GNSS receivers have broadened their application field not only in positioning and navigation, but also in deformation monitoring of civil engineering structures and geohazards. Even though some consumer-grade low-cost GNSS receivers can achieve cm-level accuracy, their lower performance compared to the dual-frequency high-end GNSS receivers restricts its systematic application of GNSS technology in monitoring projects. In this study, the noise level and performance of the low-cost GNSS receivers are assessed against geodetic receivers in terms of precision and availability when subjected to different measurements conditions, such as antenna grade, satellite constellation, and base station (antenna-receiver), based on zero- and short-baseline measurements. Furthermore, a new method is developed where a dual low-cost GNSS rover-system is formed by deploying two closely spaced low-cost GNSS receivers (30 cm apart), aiming to model their common error (multipath, satellite constellation, etc.) and reduce their noise level. The analysis of the zero- and short-baseline measurements reveals the potential improvement of the precision of the low-cost receiver by using multi-GNSS measurements and the importance of using a GNSS base station with geodetic antenna. However, development of a methodology which is based on adopting the sidereal filtering and the common mode error technique for the two closely spaced low-cost GNSS receivers may lead to precision of mm-level. The proposed methodology may broaden the application of low-cost GNSS receivers in monitoring networks and mainly for slowly developed deformations. [ABSTRACT FROM AUTHOR]

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The geodetic monitoring of local displacements and deformations is often needed for civil engineering structures and natural phenomena like, for example, landslides. A local permanent GNSS (Global Navigation Satellite Systems) network can be installed: receiver positions in the interest area are estimated and monitored with respect to reference stations. Usually, GNSS geodetic receivers are adopted and provide results with accuracies at the millimeter level: however, they are very expensive and the initial cost and the risk of damage and loss can discourage this approach. In this paper the accuracy and the reliability of low-cost u-blox GNSS receivers are experimentally investigated for local monitoring. Two experiments are analyzed. In the first, a baseline (65 m long) between one geodetic reference receiver and one u-blox is continuously observed for one week: the data are processed by hourly sessions and the results provide comparisons between two processing packages and a preliminary accuracy assessment. Then, a network composed of one geodetic and two u-blox receivers is set up. One u-blox is installed on a device (slide) that allows to apply controlled displacements. The geodetic and the other u-blox (at about 130 m) act as references. The experiment lasts about two weeks. The data are again processed by hourly sessions. The estimated displacements of the u-blox on the slide are analyzed and compared with the imposed displacements. All of the results are encouraging: in the first experiment the standard deviations of the residuals are smaller than 5 mm both in the horizontal and vertical; in the second, they are slightly worse but still satisfactory (5 mm in the horizontal and 13 mm in vertical) and the imposed displacements are almost correctly identified. [ABSTRACT FROM AUTHOR]

Snowpack is an important fresh water storage; the retrieval of snow water equivalents from satellite data permits to estimate potentially available water amounts which is an essential parameter in water management plans running in several application fields (e.g., basic needs, hydroelectric, agriculture, hazard and risk monitoring, climate change studies). The possibility to assess snowpack height from Global Navigation Satellite Systems (GNSS) observations by means of the GNSS reflectometry technique (GNSS-R) has been shown by several studies. However, in general, studies are being conducted using observations collected by continuously operating reference stations (CORS) built for geodetic purposes and equipped with geodetic-grade instruments. Moreover, CORS are located on sites selected according to criteria different from those more suitable for snowpack studies. In this work, beside an overview of key elements of GNSS reflectometry, single-frequency GNSS observations collected by u-blox M8T GNSS receivers and patch antennas from u-blox and Tallysman have been considered for the determination of antenna height from the snowpack surface on a selected test site. Results demonstrate the feasibility of GNSS-R even with non-geodetic-grade instruments, opening the way towards diffuse GNSS-R targeted applications. [ABSTRACT FROM AUTHOR]