A Map-aided GNSS Positioning Method of EoT (End-of-Train) Units for Train Integrity Monitoring

Author(s):  
Jiang Liu ◽  
Bai-gen Cai ◽  
De-biao Lu ◽  
Dirk Spiegel ◽  
Jian Wang
Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2835 ◽  
Author(s):  
Bo Chen ◽  
Chengfa Gao ◽  
Yongsheng Liu ◽  
Puyu Sun

The Global Navigation Satellite System (GNSS) positioning technology using smartphones can be applied to many aspects of mass life, and the world’s first dual-frequency GNSS smartphone Xiaomi MI 8 represents a new trend in the development of GNSS positioning technology with mobile phones. The main purpose of this work is to explore the best real-time positioning performance that can be achieved on a smartphone without reference stations. By analyzing the GNSS raw measurements, it is found that all the three mobile phones tested have the phenomenon that the differences between pseudorange observations and carrier phase observations are not fixed, thus a PPP (precise point positioning) method is modified accordingly. Using a Xiaomi MI 8 smartphone, the modified real-time PPP positioning strategy which estimates two clock biases of smartphone was applied. The results show that using multi-GNSS systems data can effectively improve positioning performance; the average horizontal and vertical RMS positioning error are 0.81 and 1.65 m respectively (using GPS, BDS, and Galileo data); and the time required for each time period positioning errors in N and E directions to be under 1 m is less than 30s.


2021 ◽  
Vol 14 (1) ◽  
pp. 44
Author(s):  
Kan Wang ◽  
Ahmed El-Mowafy ◽  
Weijin Qin ◽  
Xuhai Yang

Nowadays, integrity monitoring (IM) is required for diverse safety-related applications using intelligent transport systems (ITS). To ensure high availability for road transport users for in-lane positioning, a sub-meter horizontal protection level (HPL) is expected, which normally requires a much higher horizontal positioning precision of, e.g., a few centimeters. Precise point positioning-real-time kinematic (PPP-RTK) is a positioning method that could achieve high accuracy without long convergence time and strong dependency on nearby infrastructure. As the first part of a series of papers, this contribution proposes an IM strategy for multi-constellation PPP-RTK positioning based on global navigation satellite system (GNSS) signals. It analytically studies the form of the variance-covariance (V-C) matrix of ionosphere interpolation errors for both accuracy and integrity purposes, which considers the processing noise, the ionosphere activities and the network scale. In addition, this contribution analyzes the impacts of diverse factors on the size and convergence of the HPLs, including the user multipath environment, the ionosphere activity, the network scale and the horizontal probability of misleading information (PMI). It is found that the user multipath environment generally has the largest influence on the size of the converged HPLs, while the ionosphere interpolation and the multipath environments have joint impacts on the convergence of the HPL. Making use of 1 Hz data of Global Positioning System (GPS)/Galileo/Beidou Navigation Satellite System (BDS) signals on L1 and L5 frequencies, for small- to mid-scaled networks, under nominal multipath environments and for a horizontal PMI down to , the ambiguity-float HPLs can converge to 1.5 m within or around 50 epochs under quiet to medium ionosphere activities. Under nominal multipath conditions for small- to mid-scaled networks, with the partial ambiguity resolution enabled, the HPLs can converge to 0.3 m within 10 epochs even under active ionosphere activities.


2020 ◽  
Vol 73 (6) ◽  
pp. 1202-1222 ◽  
Author(s):  
Hoi-Fung Ng ◽  
Guohao Zhang ◽  
Li-Ta Hsu

Global navigation satellite system (GNSS) positioning in dense urban areas remains a challenge due to the signal reflection by buildings, namely multipath and non-line-of-sight (NLOS) reception. These effects degrade the performance of low-cost GNSS receivers such as in those smartphones. An effective three-dimensional (3D) mapping aided GNSS positioning method is proposed to correct the NLOS error. Instead of applying ray-tracing simulation, the signal reflection points are detected based on a skyplot with the surrounding building boundaries. The measurements of the direct and reflected signals can thus be simulated and further used to determine the user's position based on the measurement likelihood between real measurements. Verified with real experiments, the proposed algorithm is able to reduce the computational load greatly while maintaining a positioning accuracy within 10 metres of error in dense urban environments, compared with the conventional method of ray-tracing based NLOS corrected positioning.


2019 ◽  
Vol 94 ◽  
pp. 01022 ◽  
Author(s):  
Brian Bramanto ◽  
Irwan Gumilar ◽  
Muhammad Taufik ◽  
I Made D. A. Hermawan

In Indonesia, Global Navigation Satellite System (GNSS) has become one of the important tool in survey mapping, especially for cadastral purposes like land registration by using Real Time Kinematic (RTK) GNSS positioning method. The conventional RTK GNSS positioning method ensure high accuracy GNSS position solution (within several centimeters) for baseline less than 20 kilometers. The problems of resolving high accuracy position for a greater distance (more than 50 kilometers) becomes greater challenge. In longer baseline, atmospheric delays is a critical factor that influenced the positioning accuracy. In order to reduce the error, a modified LAMBDA ambiguity resolution, atmospheric correction and modified kalman filter were used in this research. Thus, this research aims to investigate the accuracy of estimated position and area in respect with short baseline RTK and differential GNSS position solution by using NAVCOM SF-3040. The results indicate that the long-range single baseline RTK accuracy vary from several centimeters to decimeters due to unresolved biases.


Author(s):  
Yanlei Gu ◽  
Li-Ta Hsu ◽  
Shunsuke Kamijo

Accurate vehicle localization technologies are significant for current onboard navigation systems and future autonomous vehicles. More specifically, positioning accuracy is expected at the submeter level. This paper presents an accurate vehicle self-localization system and evaluates the proposed system in different classes of urban environments. The developed system adopts an innovative global navigation satellite system (GNSS) positioning method as the key technique. The GNSS positioning method can improve the positioning error by reducing the effects of multipath interference and non-line-of-sight errors with the aid of a three-dimensional map. To improve positioning accuracy further, the vehicle localization system integrates the GNSS positioning technique with inertial sensors and vision sensors by considering the characteristics of each sensor. The inertial sensors represent vehicle movement with heading direction and vehicle speed. The vision sensor is used to recognize the position change relative to lane markings on the road surface. Those techniques and sensors collaborate to provide an accurate position in the global coordinate system. To verify the effectiveness and stability of the proposed system, a series of tests was conducted in one of the most challenging urban cities, Tokyo. The experiment results demonstrate that the proposed system can achieve submeter accuracy for the positioning error mean and has a 90% correct lane rate in the localization.


Sign in / Sign up

Export Citation Format

Share Document