scholarly journals Implementation and Flight Test Performance Analysis of vSLAM Aided Integrated Navigation System for Rotary UAV

2011 ◽  
Vol 39 (4) ◽  
pp. 362-369
Author(s):  
Suk-Chang Yun ◽  
Byoung-Jin Lee ◽  
Suk-Hwan Yun ◽  
Young-Jae Lee ◽  
Sang-Kyung Sung
Keyword(s):  
Performance Analysis ◽  
Navigation System ◽  
Test Performance ◽  
Flight Test ◽  
Integrated Navigation ◽  
Integrated Navigation System

scholarly journals Performance analysis of GPS / Radar integrated navigation system

2019 ◽  
Vol 94 ◽  
pp. 02006
Author(s):  
Gwang Hee Jo ◽  
Jin Hyuk Lee ◽  
Jae Hee Noh ◽  
Ju Hyun Lee ◽  
Jae Min Ahn ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Navigation System ◽  
Urban Canyon ◽  
Integrated Navigation ◽  
Radar Measurement ◽  
Integration Algorithm ◽  
Multipath Effect ◽  
Integrated Navigation System

GPS is used in various navigation fields. However, visibility is lowered in such an environment as urban canyon, and navigation performance deteriorates due to the visibility, multipath effect. So, in order to improve navigation performance in this environment, methods of integration with other sensors have been studied. In this paper, we use radar to measure the range of the landmark with known position. An integration algorithm is designed using GPS pseudorange and radar measurement.

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.

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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