Single-Frequency GNSS Positioning for Assisted, Cooperative and Autonomous Driving

2017 ◽  
Author(s):  
Peter F. de Bakker ◽  
Christian C.J.M. Tiberius
Keyword(s):  
Autonomous Driving ◽  
Single Frequency ◽  
Gnss Positioning

scholarly journals An Improved Ambiguity-Free Method for Precise GNSS Positioning with Utilizing Single Frequency Receivers

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 856 ◽  
Author(s):  
Wenhao Yang ◽  
Yue Liu ◽  
Fanming Liu
Keyword(s):  
Global Optimum ◽  
Ambiguity Function ◽  
Single Frequency ◽  
Density Estimator ◽  
New Approach ◽  
Gnss Positioning ◽  
Cycle Slips ◽  
Computation Efficiency ◽  
Ambiguity Fixing ◽  
Computation Load

The solution of carrier phase ambiguity is essential for precise global navigation satellite system (GNSS) positioning. Methods of searching in the coordinate domain show their advantage over the methods based on ambiguity fixing, for example, immune to cycle slips, far fewer epochs taken for obtaining the precise solution. However, there are still some drawbacks via using the Ambiguity Function Method (AFM), such as low computation efficiency and the existence of a false global optimum. The false global optimum is a situation where the Least Square (LS) criterion achieves minimum in another place than the point of the actual position, which restricts the application of this method to single-frequency receivers. The numerical search approach derived in this paper is based on the Modified Ambiguity Function Approach (MAFA). It focuses on eliminating the false optimum solution and reducing the computation load by utilizing single-frequency receivers without solving the ambiguity fixing problem. An improved segmented simulated annealing method is used to decrease the computation load while the Kernel Density Estimator (KDE) method is used to filter out the false optimum candidates. Static experiments were carried out to evaluate the performance of the new approach. It is shown that a precise result can be obtained by handling two epochs of data with z coordinate fixed to the referenced value. Meanwhile, the new approach can achieve a millimeter level of position accuracy after dealing with nineteen epochs of observations data when searching in x , y , z domain. The new approach shows its robustness even if the search region is broad, and the prior position is several meters away from the referenced value.

scholarly journals Preliminary Results of the Development of a Single-Frequency GNSS RTK-Based Autonomous Driving System for a Speed Sprayer

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Joong-hee Han ◽  
Chi-ho Park ◽  
Young-Jin Park ◽  
Jay Hyoun Kwon
Keyword(s):  
Tracking System ◽  
Autonomous Driving ◽  
Single Frequency ◽  
Positional Accuracy ◽  
Driving System ◽  
Preliminary Results ◽  
Skilled Manpower ◽  
Aging Populations ◽  
Fruit Orchards ◽  
Autonomous Driving System

The speed sprayer plays an important role in fruit orchards as it undertakes spraying to prevent damage by blight and harmful insects. Although farmers who use speed sprayers wear protective devices, pesticide poisoning incidents and damage can occur when pesticides penetrate the skin. In addition, skilled manpower in agriculture is decreasing due to aging populations in farming villages. To overcome these problems, we aim to develop an autonomous driving system using a single-frequency GNSS RTK for commercialization of an autonomous driving speed sprayer. Therefore, in this study, path generation and a tracking system based on the single-frequency GNSS RTK are developed and the preliminary results of tests of this system are analyzed. The field test of the developed system showed positional accuracy of 0.01 m.

scholarly journals An SVM Based Weight Scheme for Improving Kinematic GNSS Positioning Accuracy with Low-Cost GNSS Receiver in Urban Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7265
Author(s):  
Zhitao Lyu ◽  
Yang Gao
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Urban Environments ◽  
Least Square ◽  
Single Frequency ◽  
Line Of Sight ◽  
Support Vector ◽  
Positioning Accuracy ◽  
Gnss Receiver ◽  
Gnss Positioning

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.

Precise ionosphere-free single-frequency GNSS positioning

GPS Solutions ◽  
2010 ◽  
Vol 15 (2) ◽  
pp. 139-147 ◽  
Author(s):  
Torben Schüler ◽  
Herman Diessongo ◽  
Yaw Poku-Gyamfi
Keyword(s):  
Single Frequency ◽  
Gnss Positioning

scholarly journals Evaluation of Ionospheric Delay Effects on Multi-GNSS Positioning Performance

2019 ◽  
Vol 11 (2) ◽  
pp. 171 ◽  
Author(s):  
Ke Su ◽  
Shuanggen Jin ◽  
M. Hoque
Keyword(s):  
Ionospheric Delay ◽  
Convergence Time ◽  
Single Frequency ◽  
Dual Frequency ◽  
Gnss Positioning ◽  
Processing Strategies ◽  
Ionospheric Models ◽  
Delay Effects ◽  
Point Positioning ◽  
Better Than

Ionospheric delay is a significant error source in multi-GNSS positioning. We present different processing strategies to fully exploit the ionospheric delay effects on multi-frequency and multi-GNSS positioning performance, including standard point positioning (SPP) and precise point positioning (PPP) scenarios. Datasets collected from 10 stations over thirty consecutive days provided by multi-GNSS experiment (MGEX) stations were used for single-frequency SPP/PPP and dual-frequency PPP tests with quad-constellation signals. The experimental results show that for single-frequency SPP, the Global Ionosphere Maps (GIMs) correction achieves the best accuracy, and the accuracy of the Neustrelitz TEC model (NTCM) solution is better than that of the broadcast ionospheric model (BIM) in the E and U components. Eliminating ionospheric parameters by observation combination is equivalent to estimating the parameters in PPP. Compared with the single-frequency uncombined (UC) approach, the average convergence time of PPP with the external ionospheric models is reduced. The improvement in BIM-, NTCM- and GIM-constrained quad-constellation L2 single-frequency PPP was 15.2%, 24.8% and 28.6%, respectively. The improvement in convergence time of dual-frequency PPP with ionospheric models was different for different constellations and the GLONASS-only solution showed the least improvement. The improvement in the convergence time of BIM-, NTCM- and GIM-constrained quad-constellation L1/L2 dual-frequency PPP was 5.2%, 6.2% and 8.5%, respectively, compared with the UC solution. The positioning accuracy of PPP is slightly better with the ionosphere constraint and the performance of the GIM-constrained PPP is the best. The combination of multi-GNSS can effectively improve the positioning performance.

Sign in / Sign up

Export Citation Format

Share Document