Abstract
Global navigation satellite system (GNSS) is widely regarded as the primary positioning solution for intelligent transport system (ITS) applications. However, its performance could degrade, due to signal outages and faulty-signal contamination, including multipath and non-line-of-sight reception. Considering the limitation of the performance and computation loads in mass-produced automotive products, this research investigates the methods for enhancing GNSS-based solutions without significantly increasing the cost for vehicular navigation system. In this study, the measurement technique of the odometer in modern vehicle designs is selected to integrate the GNSS information, without using an inertial navigation system. Three techniques are implemented to improve positioning accuracy; (a) Time-differenced carrier phase (TDCP) based filter: A state-augmented extended Kalman filter is designed to incorporate TDCP measurements for maximizing the effectiveness of phase-smoothing; (b) odometer-aided constraints: The aiding measurement from odometer utilizing forward speed with the lateral constraint enhances the state estimation; the information based on vehicular motion, comprising the zero-velocity constraint, fault detection and exclusion, and dead reckoning, maintains the stability of the positioning solution; (c) robust regression: A weighted-least-square based robust regression as a measurement-quality assessment is applied to adjust the weightings of the measurements adaptively. Experimental results in a GNSS-challenging environment indicate that, based on the single-point-positioning mode with an automotive-grade receiver, the combination of the proposed methods presented a root-mean-square error of 2.51 m, 3.63 m, 1.63 m, and 1.95 m for the horizontal, vertical, forward, and lateral directions, with improvements of 35.1%, 49.6%, 45.3%, and 21.1%, respectively. The statistical analysis exhibits 97.3% state estimation result in the horizontal direction for the percentage of epochs that had errors of less than 5 m, presenting that after the intervention of proposed methods, the positioning performance can fulfill the requirements for road level applications.
Highlights
To realize safe intelligent transportation systems (ITS), the demand for land vehicle navigation has been rapidly increasing
Code measurement is preferred for position estimation because it does not contain integer ambiguities, and meter-level accuracy can be expected from the single-point positioning (SPP) technique in open-sky environments [1]
The position-domain phase-smoothing method utilizes time-differenced carrier phase (TDCP) measurements as a constraint of the current position relative to the previous position. This epoch-to-epoch position change can be determined to the level of TDCP accuracy through the observables directly related to the position increment [7]
Summary
To realize safe intelligent transportation systems (ITS), the demand for land vehicle navigation has been rapidly increasing. The range measurement error, caused by the NLOS reception, is equal to the additional path delay, which is the difference between the length of the path taken by the reflected signal, and the blocked-direct path, between the satellite and the receiver antenna [4,8] In this situation, because the code and the carrier are affected in the same manner, the phase-smoothing techniques, including TDCP, cannot improve the position estimation. In the multi-sensor aiding technique, some of the methods utilize additional information from other sensors, such as LiDAR, camera, or 3D-building models to detect the NLOS signals [20,21,22,23,24,25,26] It cannot discriminate multipath-contaminated signals from the received group, and suffers from cost and computational challenges, thereby, limiting their application in current consumer products. Tmhoisdreelse. arch investigates the feasibility of a cost-effective onboard solution for land-vehicle navigation applications without integrating INS and complex statistical models
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
