In recent years, due to the increase in providers of orbit and clock corrections of satellites for data evaluation in real-time and post-processing the method of Precise Point Positioning (PPP) using measurements of Global Navigation Satellite System (GNSS) and Web-based online positioning services have become widespread. Owing to some advantages, such as work-duration and cost-effectiveness, many of users have implemented PPP method instead of the traditional relative positioning method for several applications. On GNSS applications the quality of satellite ephemerides products used for data evaluation is a significant factor that affects the results in post-processing solutions either applying relative or PPP methods on analyses. These products, classified as ultra-rapid, rapid and final orbits, are regularly provided by several national and international organizations to the users. In this paper, the accuracy of PPP method has been studied comparing the outcomes from various online Web services using different software and satellite ephemerides products. For this purpose, three test points were established in a place with completely free satellite visibility (AC01) and on the other two places with partially (YC01) and vastly (KC01) prevention of satellite signals near and within a forest area at Campus of Davutpaşa of the Yildiz Technical University in Istanbul. At these stations, static observations have been conducted with a time span of 6 hours on 4th May 2015. The dataset collected using Topcon HiperPro receiver, a receiver for GPS and GLONASS data, was evaluated manually by means of the Bernese v5.2 (BSW) and GIPSY-OASIS v6.3 (Gipsy) scientific software. Moreover, the GNSS data were also proceeded using six different Web-based online services (AUSPOS, OPUS, CSRS-PPP, APPS, GAPS, Trimble-RTX) with ultra-rapid, rapid and final satellite ephemerides products. For the station with free satellite visibility (AC01), the analyses of outcomes indicate a coordinate accuracy of 1 cm for Web-based and manual data processing. That suggests relative good quality of orbit and clock corrections of satellites used by online data processing services for PPP. Furthermore, for station with partially (YC01) prevention of satellite signals, manual solutions have approximately 1 cm coordinate accuracies for n, e and u components. Moreover, when we compare the results among Web-based services, AUSPOS in relative solution and TrimbleRTX in PPP solution provides the best results. Here, one must emphasize that Trimble-RTX is a Web-based processing service for GNSS data (GPS, GLONASS, BeiDou, and QZSS) and operates an own global network of approximately 100 stations around the world for this purpose. For station with vastly (KC01) prevention of satellite signals, the best solutions were provided by APPS and CSRS-PPP using PPP approach among the Web-based services. Here, Trimble-RTX could not produce any solution. These results could demonstrate the benefit of multi-constellation of GNSS in the areas with limited satellite visibility because of increasing of the number of measurements. Comparación de precisión del método de Posicionamiento Preciso frente al posicionamiento relativo a través de diferentes productos de efemérides satelitales cerca y bajo un ambiente boscosoResumenEn los años recientes, debido al incremento de operadores satelitales de corrección de órbita y tiempo para la evaluación de información en tiempo real y de postproceso, se ha generalizado el método de posicionamiento preciso (PPP, del inglés Precise Point Positioning) que utiliza medidas del Sistema Global de Navegación por Satélite (GNSS, del inglés Global Navigation Satellite System) y servicios web de posicionamiento en línea. Debido a ventajas como el tiempo de ejecución y la relación costo-efectividad, muchos de los usuarios han implementado el método PPP en varias aplicaciones antes que el método tradicional de posicionamiento relativo. En las aplicaciones GNSS, la calidad de los productos de efemérides satelitales utilizados para la evaluación de información es un factor significante que afecta los resultados en las soluciones postproceso sea con la aplicación de métodos relativos o PPP en los análisis. Estos productos, clasificados como ultrarrápidos, rápidos y de órbita final, los proveen a los usuarios diferentes organizaciones nacionales e internacionales. En este artículo se estudia la exactitud del método PPP en comparación con los resultados de varios servicios web que utilizan diferentes productos de software y de efemérides satelitales. Con este objetivo se establecieron tres puntos de evaluación: el primero en un lugar con completa visibilidad satelital (AC01) y los otros dos con parcial (YC01) y reducida (KC01) señal satelital, en los alrededores y al interior de una zona boscosa del campus de Davutpaşa , en la Universidad Técnica Yildiz de Estambul. En las estaciones se llevaron a cabo observaciones estáticas con intervalos de seis horas el 4 de mayo de 2015. La información se recolectó con el programa Topcon HiperPro, un receptor de GPS y GLONASS (sistema GNSS desarrollado por la Unión Soviética), y se evaluó manualmente con el software científico Bernese v5.2 (BSW) y GIPSY-OASIS v6.3 (GIPSY). Además, la información también se procesón con seis servicios web en línea (AUSPOS, OPUS, CSRS-PPP, APPS, GAPS, Trimble-RTX) con productos de efemérides ultrarrápidas, rápidas y finales. Para la estación con completa visibilidad satelital (AC01), el análisis de los resultados indican una precisión coordinada de 1 cm en los procesamientos web y manual. Esto sugiere una buena calidad de las correcciones satelitales de órbita y tiempo usadas...

The multipath effect in GNSS has become a robust data source thanks to GNSS Interferometric Reflectometry (GNSS-IR), which provides environment-related features by considering the interference pattern of direct and reflected signals recorded simultaneously on the antenna phase center (APC) of the GNSS receiver. When analyzing the fluctuation of the signal strength, known as signal-to-noise ratio (SNR), SNR metrics such as frequency, amplitude, and phase can be estimated. Frequency is directly related to the reflector height, which can be converted into snow-depth. However, traditional GNSS-IR approaches have limitations in retrieving environmental features, as they generally focus on a selected satellite track or use all available tracks together for a common satellite elevation angle, which can result in missing appropriate satellite elevation angle ranges for station-based retrievals, especially for non-planar surfaces. To address this issue, we proposed an approach that searches for the proper satellite elevation angle range for each satellite track to improve snow-depth retrievals. We analyzed a 31-day GNSS data from a CORS station (KARB) located in Istanbul, Turkey, including a 3-day heavy snowstorm, to prove the performance of the proposed method. The results of the proposed algorithm were compared with the traditional GNSS-IR method results and in-situ snow-depth measurements. The initial results indicate a 10.70% increase in the correlation for snow-depth estimation compared to the traditional approach using L2 SNR data. Moreover, when the results were assessed based on MAD threshold values, increasements of 4.93% and 13.84% were obtained in the correlations for L1 SNR and L2 SNR, respectively.

In the next generation, the use of dual-frequency Embedded GNSS Chipset in the smart devices, which will be widely used in engineering applications, has been used for the first time in Xiaomi Mi8. Considering this development dynamics, a kinematic test was carried out in the marine environment monitoring with a geodetic GNSS receiver and an android smartphone in Turkey Oyak Port. According to the results of the test, RMSE for horizontal coordinate components were found as 0.0423 m and 5.9493 m for reference solution and PPP-AR solution of geodetic receiver, and reference solution and PPP solution of smartphone, respectively. Moreover, the positional errors of individual epochs were computed as 0.0411 m and 4.6871 m with respect to given order. The solution obtained from Xiaomi Mi8 raw GNSS data with PPP approach provides the Order 2 for hydrographic survey standards IHO S-44 in terms of Total Horizontal Uncertainty (THU).