Research of the INS/GPS Integrated Navigation System for High Speed Trains

2008 ◽  
Author(s):  
Haitao Zhang ◽  
Jian Rong ◽  
Xiaochun Zhong
Keyword(s):  
Navigation System ◽  
High Speed ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
High Speed Trains

scholarly journals The Design and Implementation of an Inertial GNSS Odometer Integrated Navigation System Based on a Federated Kalman Filter for High-Speed Railway Track Inspection

2021 ◽  
Vol 11 (11) ◽  
pp. 5244
Author(s):  
Xinchun Zhang ◽  
Ximin Cui ◽  
Bo Huang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
High Speed ◽  
Measurement Accuracy ◽  
Railway Track ◽  
Filter Method ◽  
Integrated Navigation ◽  
High Speed Railway ◽  
Track Geometry ◽  
Integrated Navigation System

The detection of track geometry parameters is essential for the safety of high-speed railway operation. To improve the accuracy and efficiency of the state detector of track geometry parameters, in this study we propose an inertial GNSS odometer integrated navigation system based on the federated Kalman, and a corresponding inertial track measurement system was also developed. This paper systematically introduces the construction process for the Kalman filter and data smoothing algorithm based on forward filtering and reverse smoothing. The engineering results show that the measurement accuracy of the track geometry parameters was better than 0.2 mm, and the detection speed was about 3 km/h. Thus, compared with the traditional Kalman filter method, the proposed design improved the measurement accuracy and met the requirements for the detection of geometric parameters of high-speed railway tracks.

High-Speed and Robust Scene Matching Algorithm Based on ORB for SAR/INS Integrated Navigation System

2012 ◽  
Vol 241-244 ◽  
pp. 439-443
Author(s):  
Fang Chen ◽  
Yun Xi Xu
Keyword(s):  
Navigation System ◽  
High Speed ◽  
Hamming Distance ◽  
Reference Image ◽  
Integrated Navigation ◽  
Sar Images ◽  
Matching Algorithm ◽  
Integrated Navigation System ◽  
Scene Matching ◽  
Position Errors

It is important that scene matching algorithm should satisfy the requirements of real-time, robustness and high-precision for inertial integrated navigation system. And considering the serious distortion and speckle noises of SAR images, we proposed a new scene matching algorithm for the SAR/INS integrated navigation system with high-speed and robustness based on Oriented FAST and Rotated BRIEF (ORB). We started by detecting scale-space FAST-based features in combination with an efficiently computed orientation in the image. Then, we calculated feature point's Rotation-Aware BRIEF descriptor which performs well with rotation and match features by computing Hamming distance between descriptors. Finally, we adopted GroupSAC which are proposed recently to remove the false matching points and the least square algorithm for getting the distortion transformation parameters that are the aircraft position errors and rotation transform parameters between real image and reference image. Experimental results on real SAR images indicate that our algorithm is invariant to various image transformations due to rotation and scale, and also robust to speckle noise and extremely efficient to compute, better than SIFT in many situations. Therefore, our algorithm can meet the high performance needs for matching navigation in the SAR/INS integrated navigation system.

scholarly journals MEMS Based SINS/OD Filter for Land Vehicles’ Applications

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Huisheng Liu ◽  
Zengcai Wang ◽  
Susu Fang ◽  
Chao Li
Keyword(s):  
Navigation System ◽  
Velocity Measurement ◽  
Microelectromechanical Systems ◽  
Low Cost ◽  
Detection Algorithm ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Land Vehicles ◽  
Mems Imu

A constrained low-cost SINS/OD filter aided with magnetometer is proposed in this paper. The filter is designed to provide a land vehicle navigation solution by fusing the measurements of the microelectromechanical systems based inertial measurement unit (MEMS IMU), the magnetometer (MAG), and the velocity measurement from odometer (OD). First, accelerometer and magnetometer integrated algorithm is studied to stabilize the attitude angle. Next, a SINS/OD/MAG integrated navigation system is designed and simulated, using an adaptive Kalman filter (AKF). It is shown that the accuracy of the integrated navigation system will be implemented to some extent. The field-test shows that the azimuth misalignment angle will diminish to less than 1°. Finally, an outliers detection algorithm is studied to estimate the velocity measurement bias of the odometer. The experimental results show the enhancement in restraining observation outliers that improves the precision of the integrated navigation system.

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