High-Speed and Real-Time Communication Controller for Embedded Integrated Navigation System

2009 ◽  
Author(s):  
Zhang Guolong ◽  
Xu Xiaosu
Keyword(s):  
Real Time ◽  
Navigation System ◽  
High Speed ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Communication Controller

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.

An Integrated Navigation System For Suez Canal (SCINS)

2003 ◽  
Vol 56 (2) ◽  
pp. 241-255 ◽  
Author(s):  
Farouk Abd EL-Kader ◽  
M. Samy Abo EL-Soud ◽  
Kamel EL-Serafy ◽  
Ezzat A. Hassan
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Traffic Management ◽  
Filter Design ◽  
Suez Canal ◽  
System Level ◽  
Superior Performance ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Traffic Management System

This paper offers a designed Integrated Navigation System that will permit vessels to transit safely through the Suez Canal avoiding collision and grounding in all weather environments instead of being directed to anchor, thus keeping the Canal open at all times for ship transits. The Suez Canal Integrated Navigation System (SCINS) includes Differential Global Positioning System (DGPS), Suez Canal LORAN-C system, and Vessel Traffic Management System (VTMS). The combination of DGPS and LORAN-C systems would provide real-time DGPS corrections that could be used to calibrate the Loran fix; this can be achieved by means of portable integrated DGPS/LORAN-C sets installed aboard the vessels. The addition of VTMS provides significant capability for preserving system accuracy during periods of GPS outages. Due to the interface between LORAN-C and VTMS systems, the SCINS will be able to solve the problem of targets that cannot be tracked by VTMS radars in the shadow areas behind the new bridges along the Canal. The SCINS automates position fixing in real-time, offers a designed algorithm to return the ship to the middle of the Canal and computes the cross-track error (XTE) and the ship squat. Kalman Filter design and system level performance predictions for the SCINS are briefly described. Simulation results show that the SCINS offers superior performance and better position accuracy than current integrated systems.

MEMS-SINS/GPS/Magnetometer Integrated Navigation System for Small Unmanned Aerial Vehicles

2014 ◽  
Vol 568-570 ◽  
pp. 976-986 ◽  
Author(s):  
Cun Xiao Miao ◽  
Juan Juan Cao ◽  
Yang Bin Ou
Keyword(s):  
Low Power ◽  
Real Time ◽  
Navigation System ◽  
Inertial Sensors ◽  
Unscented Kalman Filter ◽  
Flight Test ◽  
Integrated Navigation ◽  
Autonomous Flight ◽  
Integrated Navigation System ◽  
Small Uav

The constraints of weight, volume and power for Small unmanned air vehicle (UAV) restrict the application of sensors with heavy and good performance and powerful processors. This paper presents a real-time solution of autonomous flight navigation and its results for small UAV by applying small, cheap, low precision and low-power integrated navigation system, which includes Strap-down Inertial Navigation System (SINS) based on Micro-electro-mechanical system (MEMS) inertial sensors, Global Positioning System (GPS) receiver and magnetometer. The Square-Root Unscented Kalman filter (SR-UKF) for data fusion using in this MEMS-SINS/GPS/ magnetometer integrated navigation system provides continuous and reliable navigation results for the loops of guidance and control for the small UAV with autonomous flight. The whole integrated navigation system algorithm is implemented within low-power embedded microprocessors. The real-time flight test results show that the MEMS-SINS/GPS/magnetometer integrated navigation system is effective and accurate.

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