Application of system fault detection and intelligent reconstruction method based on machine learning in micro inertial pedestrian navigation system

Author(s):  
Cui-hong GU ◽  
Wei-xing QIAN ◽  
Shu-qin YANG ◽  
Xin CHEN ◽  
Er-peng WANG ◽  
...  
2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaoyue Zhang ◽  
Pengbo Liu ◽  
Chunxi Zhang

To ensure the high accuracy, independence, and reliability of the measurement system in the unmanned aerial vehicle (UAV) landing process, an integration method of inertial navigation system (INS) and the three-beam Lidar is proposed. The three beams of Lidar are, respectively, regarded as an independent sensor to integrate with INS according to the conception of multisensor fusion. Simultaneously, the fault-detection and reconstruction method is adopted to enhance the reliability and fault resistance. First the integration method is described. Then the strapdown inertial navigation system (SINS) error model is introduced and the measurement model of SINS/Lidar integrated navigation is deduced under Lidar reference coordinate. The fault-detection and reconstruction method is introduced. Finally, numerical simulation and vehicle test are carried out to demonstrate the validity and utility of the proposed method. The results indicate that the integration can obtain high precision navigation information and the system can effectively distinguish the faults and accomplish the reconstruction to guarantee the normal navigation when one or two beams of the Lidar malfunction.


2019 ◽  
Vol 23 (4) ◽  
pp. 1136-1148
Author(s):  
Gopalakrishnan K ◽  
Thiruvenkatasamy S ◽  
Prabhakar E ◽  
Aarthi R

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Wanling Li ◽  
Zhi Xiong ◽  
Yiming Ding ◽  
Zhiguo Cao ◽  
Zhengchun Wang

2021 ◽  
Vol 1964 (5) ◽  
pp. 052015
Author(s):  
S Muthukrishnan ◽  
Arun Kumar Pallekonda ◽  
R Saravanan ◽  
B Meenakshi

2021 ◽  
Author(s):  
Yang Meng ◽  
Xinyun Wu ◽  
Jumoke Oladejo ◽  
Xinyue Dong ◽  
Zhiqian Zhang ◽  
...  

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