scholarly journals Particle Filter for Positioning Accuracy Improvement in GNSS Receiver

2013 ◽  
Author(s):  
Xiaowen Sun ◽  
Shufang Zhang ◽  
Qing Hu
Keyword(s):  
Particle Filter ◽  
Accuracy Improvement ◽  
Positioning Accuracy ◽  
Gnss Receiver

Positioning Accuracy Improvement of Automated Guided Vehicles Based on a Novel Magnetic Tracking Approach

2020 ◽  
Vol 12 (4) ◽  
pp. 138-148 ◽  
Author(s):  
Shijian Su ◽  
Xianping Zeng ◽  
Shuang Song ◽  
Mingqiang Lin ◽  
Houde Dai ◽  
...  
Keyword(s):  
Automated Guided Vehicles ◽  
Accuracy Improvement ◽  
Positioning Accuracy ◽  
Magnetic Tracking

Positioning accuracy improvement in five-axis milling by post processing

1997 ◽  
Vol 37 (2) ◽  
pp. 223-236 ◽  
Author(s):  
R.M.D. Mahbubur ◽  
J. Heikkala ◽  
K. Lappalainen ◽  
J.A. Karjalainen
Keyword(s):  
Post Processing ◽  
Accuracy Improvement ◽  
Positioning Accuracy ◽  
Five Axis

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.

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