scholarly journals The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System

2018 ◽  
Author(s):  
Wenwen Liu ◽  
Yuanchang Liu ◽  
Rui Song ◽  
Richard Bucknall
Keyword(s):  
Operating System ◽  
Data Fusion ◽  
Real Time ◽  
Sensor Data ◽  
Vehicle Navigation ◽  
Fusion System ◽  
Unmanned Surface Vehicle ◽  
Real Time Operating System ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion

scholarly journals Real-Time Onboard 3D State Estimation of an Unmanned Aerial Vehicle in Multi-Environments Using Multi-Sensor Data Fusion

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 919 ◽  
Author(s):  
Hao Du ◽  
Wei Wang ◽  
Chaowen Xu ◽  
Ran Xiao ◽  
Changyin Sun
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Position Estimation ◽  
Sensor Data ◽  
Measurement Unit ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Aerial Vehicle

The question of how to estimate the state of an unmanned aerial vehicle (UAV) in real time in multi-environments remains a challenge. Although the global navigation satellite system (GNSS) has been widely applied, drones cannot perform position estimation when a GNSS signal is not available or the GNSS is disturbed. In this paper, the problem of state estimation in multi-environments is solved by employing an Extended Kalman Filter (EKF) algorithm to fuse the data from multiple heterogeneous sensors (MHS), including an inertial measurement unit (IMU), a magnetometer, a barometer, a GNSS receiver, an optical flow sensor (OFS), Light Detection and Ranging (LiDAR), and an RGB-D camera. Finally, the robustness and effectiveness of the multi-sensor data fusion system based on the EKF algorithm are verified by field flights in unstructured, indoor, outdoor, and indoor and outdoor transition scenarios.

Study on Leak Detecting System for Oil Pipeline Based on Multi-Sensor Data Fusion Technique

2012 ◽  
Vol 220-223 ◽  
pp. 1898-1901
Author(s):  
Jie Zhang ◽  
Xiao Wang ◽  
Zhen Zhao
Keyword(s):  
Wavelet Transform ◽  
Data Fusion ◽  
Real Time ◽  
Sensor Data ◽  
Time Signal ◽  
Fusion Technology ◽  
Transform Method ◽  
Oil Pipeline ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion

In this paper, based on the wavelet transform method, the multi-sensor data fusion technology is adopted to solve some key problems in pipeline leak detection system. Compared with the traditional filtering method, the wavelet transform method can better remove the pipeline leakage signal noise. When the corresponding wavelet is selected, after FPGA realized, the method has the advantages of fast speed, arbitrarily data width set, which can better meet the needs of real-time signal processing requirements of pipeline leak. At the same time, VHDL language has the characteristics of portability, greater generality. When multi-sensor fusion technology is used in the paper, the relation, correlation, estimation and integrated processing is done in turn to the information from multiple data sources, the system can achieve better detection performance than a system using the single sensor, so as to form a more complete, reliable pipeline real time detecting conclusion.

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