Positioning Performance Evaluation of Automotive Grade Chipsets

Nataliya Mishukova, Stefan Junker and Ramzi El Khayat

Abstract: The emerging automotive applications raised the necessity for a reliable highly accurate absolute GNSS positioning which is a critical requirement for autonomous vehicles. With the purpose of meeting the mass market demands, these applications require the use of automotive-grade GNSS chipsets that usually follow a trade-off between availability of the measurements, measurement quality, power consumption, and production cost. We demonstrate the positioning performance of Trimble’s next generation precise positioning engine by means of the measurements of three different automotive-grade GNSS receiver chipsets. These chipsets track selected frequency bands for each constellation reaching at most two frequencies per system and varying from one chipset to another. The data used in the analysis was collected in kinematic scenarios in a multitude of environments like canopy, suburban, and highway, without the use of inertial measurement units data or integrated cameras. The possibility of precise, accurate and reliable GNSS positioning performance with low-cost GNSS receivers has been proved in open-sky and less obstructed environments in the past. However extending the field of application of such receivers to Advanced Driver Assistance Systems (ADAS) as well as fully Autonomous Driving (AD) systems requires broadening the focus of the analysis and development to more challenging environments. The paper will show that reliable and highly accurate positioning based solely on GNSS measurements is feasible in such environments in real-time. For the different analyses performed, we employ the Trimble Real Time eXtended (RTX) stream, a globally available correction service enabling a centimeter accurate positioning in real-time without the need for a local base station. RTX data is delivered via satellite or Internet Protocol (IP), and provides redundant information in safety critical applications. We start by evaluating the code and phase noise of the different receivers to get a general idea of the state of the art measurement quality provided by automotive-grade GNSS chipsets. We then show the benefit of regional augmented correction data (CenterPoint® RTX Fast) compared to standard correction service (CenterPoint® RTX) in the scope of the automotive market requirements, especially the need for fast re-convergence of the positioning solution after signal loss due to underpasses or tunnels. Re-convergence below 20cm using CenterPoint® RTX Fast corrections is done within a few seconds, while re-convergence with standard corrections can take several minutes. Furthermore, we analyze the impact of extending the automotive-grade chipsets with a second frequency band. We will show that this development is one of the key features for high precise positioning leading to positioning errors of less than 10 cm at 1 sigma in all target environments. Finally, we demonstrate the ability to achieve 20cm horizontal positioning error at 2 sigma in canopy, suburban and highway environments and show that a re-convergence to 20cm horizontal positioning error at 2 sigma after interruptions on highways (bridges, traffic signs) is feasible within 10 seconds using only GNSS measurements.
Published in: Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)
September 16 - 20, 2019
Hyatt Regency Miami
Miami, Florida
Pages: 221 - 245
Cite this article: Mishukova, Nataliya, Junker, Stefan, Khayat, Ramzi El, "Positioning Performance Evaluation of Automotive Grade Chipsets," Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019), Miami, Florida, September 2019, pp. 221-245.
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