Research on Navigation Algorithm of UAV Optical Flow/Inertia Multi-Information Fusion

2020 ◽  
Author(s):  
Di Chen ◽  
Kun Qian ◽  
Kaijun Liao ◽  
Yu Zhu
Keyword(s):  
Optical Flow ◽  
Information Fusion ◽  
Navigation Algorithm ◽  
Flow Inertia

Simulation of Accurate Navigation Technology for Aircraft Landing Approach

2013 ◽  
Vol 329 ◽  
pp. 406-410
Author(s):  
Ang Tai Li ◽  
Xiao Jiao Ma
Keyword(s):  
Information Fusion ◽  
Navigation System ◽  
Location Information ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
System Models ◽  
Navigation Algorithm ◽  
Aircraft Landing ◽  
Simulation Results

The purpose of this paper is to find a solid application and improve the integrated navigation system of aircraft independent landing. The main researches are focused on the issue how to improve the accuracy and reliability of the integrated navigation system, by means of the detailed analyzing about information fusion, and investigating accurate navigation technology for independent landing approach of aircraft. Next, the integrated navigation system models SINS/DGPS/TAN/ILS based on Federated filter are established, and the accurate navigation algorithm of landing is also researched. At the end, the paper gives its simulation results for independent lading approach, which show this algorithm is able to greatly improve the accuracy of speed and location information for aircraft accurate landing.

scholarly journals Operational Deflection Shapes Magnification and Visualization Using Optical-Flow-Based Image Processing

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8351
Author(s):  
Adam Machynia ◽  
Ziemowit Dworakowski ◽  
Kajetan Dziedziech ◽  
Paweł Zdziebko ◽  
Jarosław Konieczny ◽  
...  
Keyword(s):  
Optical Flow ◽  
Information Fusion ◽  
Real Life ◽  
Cantilever Beams ◽  
Points Of Interest ◽  
Source Data ◽  
Flow Information ◽  
Motion Magnification ◽  
Definition Of ◽  
General Motion

Much information can be derived from operational deflection shapes of vibrating structures and the magnification of their motion. However, the acquisition of deflection shapes usually requires a manual definition of an object’s points of interest, while general motion magnification is computationally inefficient. We propose easy extraction of operational deflection shapes straight from vision data by analyzing and processing optical flow information from the video and then, based on these graphs, morphing source data to magnify the shape of deflection. We introduce several processing routines for automatic masking of the optical flow data and frame-wise information fusion. The method is tested based on data acquired both in numerical simulations and real-life experiments in which cantilever beams were subjected to excitation around their natural frequencies.

Optical flow-aided navigation for UAV: A novel information fusion of integrated MEMS navigation system

Optik ◽  
2016 ◽  
Vol 127 (1) ◽  
pp. 447-451 ◽  
Author(s):  
Ling Zhang ◽  
Zhi Xiong ◽  
Jizhou Lai ◽  
Jianye Liu
Keyword(s):  
Optical Flow ◽  
Information Fusion ◽  
Navigation System

Motion correction in PET/CT

2005 ◽  
Vol 44 (S 01) ◽  
pp. S46-S50 ◽  
Author(s):  
M. Dawood ◽  
N. Lang ◽  
F. Büther ◽  
M. Schäfers ◽  
O. Schober ◽  
...  
Keyword(s):  
Optical Flow ◽  
Motion Correction ◽  
Motion Vector ◽  
Emission Tomography ◽  
Cardiac Pet ◽  
Novel Approach ◽  
Positron Emission ◽  
Pet Ct ◽  
Flow Algorithm ◽  
Motion Vector Field

Summary:Motion in PET/CT leads to artifacts in the reconstructed PET images due to the different acquisition times of positron emission tomography and computed tomography. The effect of motion on cardiac PET/CT images is evaluated in this study and a novel approach for motion correction based on optical flow methods is outlined. The Lukas-Kanade optical flow algorithm is used to calculate the motion vector field on both simulated phantom data as well as measured human PET data. The motion of the myocardium is corrected by non-linear registration techniques and results are compared to uncorrected images.

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