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In August 2023, Xiaomi unveiled the Redmi K60 Ultra, the first multi-frequency smartphone integrated with BeiDou-3 Navigation Satellite System Precise Point Positioning (PPP-B2b) services and employing PPP technology as the primary positioning method. The positioning enhancement service is provided by the Assisted Global Navigation Satellite System (A-GNSS) location platform developed by the China Academy of Information and Communications Technology. The signaling interaction between the server and the users strictly adheres to the Third Generation of Mobile Communications Technology Partnership Project Long-Term Evolution Positioning Protocol and the Open Mobile Alliance Secure User Plane Location framework. To comprehensively evaluate the Redmi K60 Ultra's capabilities, this study designed six distinct experimental scenarios and conducted comprehensive research on multi-frequency and multi-GNSS observation noise, Time to First Fix (TTFF), as well as the performance of both GNSS-based and network-based positioning. Experimental results indicate that the GNSS chipset within the Redmi K60 Ultra has achieved a leading position in the consumer market concerning supported satellite constellations, frequencies, and observation accuracy, and is comparable to some low-cost GNSS receivers. A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a standalone GNSS mode. The positioning results show that the A-GNSS PPP-B2b service can achieve positioning performance with RMS errors of less than 1.5 m, 2.5 m, and 4 m in open-sky, realistic, and challenging urban environments. Compared to GNSS-based positioning, cellular network-based Observed Time Difference of Arrival (OTDOA) positioning achieves an accuracy ranging from tens to hundreds of meters in various experimental scenarios and currently functions primarily as coarse location determination. Additionally, this study explores the potential of the Three-Dimensional Mapping-Aided (3DMA) GNSS algorithm in detecting Non-Line-of-Sight signals and enhancing positioning performance. The results indicate that 3DMA PPP, as compared to conventional PPP, can significantly accelerate PPP convergence and improve positioning accuracy by over 30%. Consequently, 3D city models can be utilized as future assistance data for the A-GNSS location platform. [ABSTRACT FROM AUTHOR]

Abstract In August 2023, Xiaomi unveiled the Redmi K60 Ultra, the first multi-frequency smartphone integrated with BeiDou-3 Navigation Satellite System Precise Point Positioning (PPP-B2b) services and employing PPP technology as the primary positioning method. The positioning enhancement service is provided by the Assisted Global Navigation Satellite System (A-GNSS) location platform developed by the China Academy of Information and Communications Technology. The signaling interaction between the server and the users strictly adheres to the Third Generation of Mobile Communications Technology Partnership Project Long-Term Evolution Positioning Protocol and the Open Mobile Alliance Secure User Plane Location framework. To comprehensively evaluate the Redmi K60 Ultra’s capabilities, this study designed six distinct experimental scenarios and conducted comprehensive research on multi-frequency and multi-GNSS observation noise, Time to First Fix (TTFF), as well as the performance of both GNSS-based and network-based positioning. Experimental results indicate that the GNSS chipset within the Redmi K60 Ultra has achieved a leading position in the consumer market concerning supported satellite constellations, frequencies, and observation accuracy, and is comparable to some low-cost GNSS receivers. A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a standalone GNSS mode. The positioning results show that the A-GNSS PPP-B2b service can achieve positioning performance with RMS errors of less than 1.5 m, 2.5 m, and 4 m in open-sky, realistic, and challenging urban environments. Compared to GNSS-based positioning, cellular network-based Observed Time Difference of Arrival (OTDOA) positioning achieves an accuracy ranging from tens to hundreds of meters in various experimental scenarios and currently functions primarily as coarse location determination. Additionally, this study explores the potential of the Three-Dimensional Mapping-Aided (3DMA) GNSS algorithm in detecting Non-Line-of-Sight signals and enhancing positioning performance. The results indicate that 3DMA PPP, as compared to conventional PPP, can significantly accelerate PPP convergence and improve positioning accuracy by over 30%. Consequently, 3D city models can be utilized as future assistance data for the A-GNSS location platform.

Indoor navigation is the most challenging environment regarding precise positioning service for a smartphone’s physical quality limitations and interferences for high buildings, trees and multipath fading in the GNSS signal received. A GPS by itself cannot offer a solution; the A-GNSS from a network mobile provided through telecommunication infrastructure provides information that is useful to counteract these issues. A smartphone has full connectivity to the mobile network 24/7 and has access to the GNSS database when required, and the assisted information is sent over an Internet Protocol (IP) and processed by the GNSS chip, increasing the accuracy, TTFF, and availability of data even in harsh environments. The outdoor, light indoor, and urban canyon scenarios are experienced when driving in some places in the city, and they are recorded with Geo++ and processed with RTKlib using a single frequency in a standalone and multi-constellation double-frequency smartphone, Xiaomi Mi 8, with A-GNSS. The results show good accuracy in the SPS for over 10 (m) and in assisted positioning over 50 (m); the TTFF in assisted positioning is always 5 (s), and in the SPS, it reaches 20 (s). Finally, during the trajectory, only the assisted positioning can compute the position; this is because of the data availability from a mobile network.

This paper evaluates and compares the static performance of low-cost and legacy geodetic multi-frequency multi-GNSS positioning device (PD) in terms of the GNSS signal strength, RTK (Real-Time-Kinematic) availability and positioning accuracy, and time to first fix (RTK-TTFF/TTRF), which were measured for short and medium baselines (SBL and MBL) with different receiver resets and GNSS signal obstructions. The evaluation results indicated that the low-cost PDs, which were combined from a single u-blox ZED-F9P receiver and multiple low-cost GNSS antennas, performed at almost the same accuracy level of the legacy PDs and were superior in term of the RTK-TTFF/TTRF performance. The low-cost PDs could track satellites of four GNSS constellations with high signal strength of about 50dB-Hz resulting in almost full-time availability of RTK-fixed solution, and millimeter-level and centimeter-level accuracy of the horizontal positioning for the SBL and MBL, respectively. Furthermore, the low-cost PDs could acquire and reacquire RTK-fixed mode in less than 12 seconds and 4 second, respectively, and hold for any significant time in static applications.

Precise point positioning (PPP) is famous for its capability of high-precision positioning and its wide application in many fields. With the rapid development of BDS and Galileo, the number of GNSS satellites used for positioning has now exceeded 110. It brings both opportunities and challenges to PPP. Based on the data of 90 tracking stations of MGEX, this paper analyzed the impact of elevation masks on the performance of multi-GNSS kinematic PPP. The results show that the PODP increases as the elevation mask increases. In general, it will reduce the positioning accuracy and the convergence speed with the increasing of the elevation mask for the PPP float solution. Furthermore, when the elevation mask is below 25o, increasing the elevation mask has little effect on the position accuracy of the horizontal and vertical components in the first 10 min. But after 15 min, the effect on the vertical component became apparently. And after convergence, the RMS of multi-GNSS PPP float solution can reach 5 cm and 10 cm for the horizontal and vertical components when the elevation mask is below 25o. When the elevation mask is 30o, the RMS is still less than 6 cm for the horizontal component, while about 99% of the RMS is less than 11.5 cm for the vertical component. Thirdly, for multi-GNSS PPP AR, it can improve the TTFF and the fixing percentage by fixing the ambiguity subnet with higher elevation mask firstly. Moreover, when the elevation mask is below to 20o, the improvement is more obvious and when the elevation mask is larger than 25o, the TTFF may become longer in some cases. [ABSTRACT FROM AUTHOR]

The Open Source GNSS Reference Server (OSGRS) exploits the GNSS Reference Interface Protocol (GRIP) to provide assistance data to GPS receivers. Assistance can be in terms of signal acquisition and in the processing of the measurement data. The data transfer protocol is based on Extensible Mark-up Language (XML) schema. The first version of the OSGRS required a direct hardware connection to a GPS device to acquire the data necessary to generate the appropriate assistance. Scenarios of interest for the OSGRS users are weak signal strength indoors, obstructed outdoors or heavy multipath environments. This paper describes an improved version of OSGRS that provides alternative assistance support from a number of Global Navigation Satellite Systems (GNSS). The underlying protocol to transfer GNSS assistance data from global casters is the Networked Transport of RTCM (Radio Technical Commission for Maritime Services) over Internet Protocol (NTRIP), and/or the RINEX (Receiver Independent Exchange) format. This expands the assistance and support model of the OSGRS to globally available GNSS data servers connected via internet casters. A variety of formats and versions of RINEX and RTCM streams become available, which strengthens the assistance provisioning capability of the OSGRS platform. The prime motivation for this work was to enhance the system architecture of the OSGRS to take advantage of globally available GNSS data sources. Open source software architectures and assistance models provide acquisition and data processing assistance for GNSS receivers operating in weak signal environments. This paper describes test scenarios to benchmark the OSGRSv2 performance against other Assisted-GNSS solutions. Benchmarking devices include the SPOT satellite messenger, MS-Based & MS-Assisted GNSS, HSGNSS (SiRFstar-III) and Wireless Sensor Networks Assisted-GNSS. Benchmarked parameters include the number of tracked satellites, the Time to Fix First (TTFF), navigation availability and accuracy. Three different configurations of Multi-GNSS assistance servers were used, namely Cloud-Client-Server, the Demilitarized Zone (DMZ) Client-Server and PC-Client-Server; with respect to the connectivity location of client and server. The impact on the performance based on server and/or client initiation, hardware capability, network latency, processing delay and computation times with their storage, scalability, processing and load sharing capabilities, were analysed. The performance of the OSGRS is compared against commercial GNSS, Assisted-GNSS and WSN-enabled GNSS devices. The OSGRS system demonstrated lower TTFF and higher availability. [ABSTRACT FROM AUTHOR]

Assisted GPS (A-GPS) has received much attention from both academic and industry because of its two major advantages, faster positioning and greater sensitivity. Secure User Plane Location (SUPL) is an emerging standard for A-GPS produced by the Open Mobile Alliance. This article briefly reviews A-GPS, then introduces the SUPL architecture and explains how SUPL works. An intensive SUPL A-GPS survey under different environments is reported in detail, while a standalone GPS test was utilized for comparison. The survey was carried out in 24 locations over the University of New South Wales campus representing 5 types of terrain: Urban, Suburban, Rural, Indoor, and Open sky with a wide range of acquisition difficulty levels. The results show SUPL can bring a great benefit in fast positioning--much shorter Time-To-First-Fix and high sensitivity--and a much lower failure rate. [ABSTRACT FROM AUTHOR]