Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

Multi-GNSS Precise Point Positioning Software Architecture and Analysis of GLONASS Pseudorange Biases

With expanding satellite-based navigation systems, multi-Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) presents an advantage over a single navigation system, which improves position accuracy and enhances availability of satellites and signals. The York GNSS PPP software was developed using C++ in the Microsoft.Net platform to utilize the existing multi-GNSS satellite constellations based on the software processor used by the Natural Resources Canada (NRCan) PPP online service. The software was built as a robust, scalable, modular tool that meets the highest of scientific standards compared to existing online PPP engines.There exists a correlation between receiver stations from heterogeneous networks, such as the IGS, in GNSS PPP processing and the increase in magnitude of the pseudorange and carrier-phase biases in both GPS + GLONASS and GLONASS-only PPP solutions. The correlation is due to mixed receiver and antenna hardware as well as firmware versions. Unlike GPS, GLONASS observations are affected by the Frequency Division Multiple Access (FDMA) satellite signal structure, which introduces inter-frequency channel biases and other system biases. The GLONASS pseudorange inter-channel frequency biases show a strong correlation with different receiver types, firmware versions and antenna types. This research estimated the GLONASS pseudorange inter-frequency channel biases using 350 IGS stations, based on 32 receiver types and 4 antenna types over a period of one week. An improvement of 19% was observed after calibrating for the pseudorange ICBs, in the horizontal components respectively, considering 20 minutes convergence period