Real time differential GPS and GLONASS vehicle positioning in urban areas

Walsh, David; Capaccio, Stefano; Lowe, David; Daly, Peter; Shardlow, Peter; Johnston, Gordon

doi:10.1109/itsc.1997.660527

Cited by 11 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One method for improving attributes of a navigation system such as accuracy, reliability and availability, through the integration of external information into the position calculation process is known as Global Navigation Satellite System (GNSS) position augmentation. Some of the widely known methods include Differential Global Navigation Satellite System (DGNSS) [ 8 ], Real-time Kinematic (RTK) [ 9 ] and Real-time eXtended (RTX) [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments

Swaminathan

Sommer

Becker

et al. 2022

Sensors

View full text Add to dashboard Cite

Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation techniques such as classical Differential Global Navigation Satellite System, Real-time Kinematic and Real-time eXtended. The aim is to understand the limitations and choose the best position augmentation technique in order to obtain accurate, trustworthy position estimates of a vehicle in urban environments. The tests are performed in and around the German cities of Wuppertal and Duesseldorf, using a vehicle fitted with the navigation system POS-LV 220, developed by Applanix Corporation. In order to evaluate the real-time performance of position augmentation techniques in a highly challenging environment, a total of four test regions are selected. The four test regions are characterized mainly by uneven terrain with tall buildings around the University of Wuppertal, flat terrain with roads of varying width in the city centre of Wuppertal and Duesseldorf and flat terrain in a tunnel section located in the city of Wuppertal. The performances of the different position augmentation are compared using a Root Mean Square (RMS) error estimate obtained as an output from the Applanix system. Furthermore, a High-Definition map of the environment is used for the purpose of model validation, which justifies the use of RMS error estimate as an evaluation metric for the performance analysis tests. According to the performance tests carried out as per the conditions specified in this paper, the Real-time eXtended (RTX) position augmentation method enables to obtain a more robust position information of the vehicle than Real-time Kinematic (RTK) method, with a typical accuracy of a few centimeter in an urban environment.

show abstract

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments

Swaminathan

Sommer

Becker

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…As a part of the vehicular network, vehicle positioning plays an important role in intelligent traffic management systems, vehicle detection, autonomous driving, intelligent parking, and so on [ 1 ]. Traditional vehicle positioning usually adopts global navigation satellite system (GNSS) represented by global positioning system (GPS), GLONASS, Beidou navigation system (BDS), and Galileo [ 2 , 3 , 4 , 5 , 6 , 7 ]. However, in urban canyon environments, GNSS signals are often blocked by high-rise buildings and perform with low capability in terms of positioning [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

Deng

Zheng

Wang

et al. 2020

Sensors

View full text Add to dashboard Cite

Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.

show abstract

“…1) To increase the number of visible satellites. In [3], [9], the Russian Global Navigation Satellite System (GLONASS) is used to augment the GPS by offering more satellites in view and thus, increasing the satellites' availability. Advanced GPS receivers [10], [11] have been developed which can access up to Manuscript received August 27, 2001.…”

Section: Introductionmentioning

confidence: 99%

Autonomous vehicle positioning with gps in urban canyon environments

Cui

2003

IEEE Trans. Robot. Automat.

258

View full text Add to dashboard Cite

The Global Positioning System (GPS) has been widely used in land vehicle navigation applications. However, the positioning systems based on GPS alone face great problems in the so-called urban canyon environments, where the GPS signals are often blocked by highrise buildings and there are not enough available satellite signals to estimate the positioning information of a fix. To solve the problem, a constrained method is presented by approximately modeling the path of the vehicle in the urban canyon environments as pieces of lines. By adding this constraint, the minimum number of available satellites reduces to two, which is satisfied in many urban canyon environments. Then, different approaches using the constrained method are systematically developed. In addition, a state-augmentation method is proposed to simultaneously estimate the positions of the GPS receiver and the parameters of the line. Furthermore, the interacting multiple model method is used to determine the correct path which the vehicle follows after passing an intersection of roads. Simulation results show that this approach can solve the urban canyon problems successfully.

show abstract

Real time differential GPS and GLONASS vehicle positioning in urban areas

Cited by 11 publications

References 1 publication

Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments

Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

Autonomous vehicle positioning with gps in urban canyon environments

Contact Info

Product

Resources

About