A system developed at The University of Texas for low-cost precise urban vehicular positioning is demonstrated to achieve a probability of correct integer fixing greater than 96.5% for a probability of incorrect integer fixing surely less than 2.3% and likely less than 1%. This is demonstrated using data captured during 3.4 hours of driving on a repeating urban test route over three separate days. The results are achieved without any aiding by inertial or electro-optical sensors. Development and evaluation of the unaided GNSS-based precise positioning system is a key milestone toward the overall goal of combining precise GNSS, vision, radar, and inertial sensing for all-weather high-integrity precise positioning for automated and connected vehicles. The system described and evaluated herein is composed of a densely-spaced reference network, a software-defined GNSS receiver whose processing can be executed on general-purpose commodity hardware, and a real-time kinematic (RTK) positioning engine. All components have been tailored in their design to yield competent sub-decimeter positioning in the mobile urban environment. A performance sensitivity analysis reveals that navigation data bit prediction on the GPS L1 C/A signals is key to high-performance urban RTK positioning.

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Todd E. Humphreys, Matthew Murrian, and Lakshay Narula "Low-cost Precise Vehicular Positioning in Urban Environments," in Proceedings of the IEEE/ION PLANS Meeting, Monterey, CA, 2018.