scholarly journals Research on Adaptive Multi-Source Information Fault-Tolerant Navigation Method Based on No-Reference System Diagnosis

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2911 ◽  
Author(s):  
Ling Zhang ◽  
Yuchen Cui ◽  
Zhi Xiong ◽  
Jianye Liu ◽  
Jizhou Lai ◽  
...  

In order to obtain accurate and optimized navigation sensor information, it is necessary to study information fusion and fault diagnosis with high reliability, high precision and high autonomy, and then to propose a rapid and accurate intelligent decision-making scheme based on multi-source and heterogeneous navigation information. In view of the existing fault-tolerant navigation federated filter structure, the method of assuming the reference system (inertial navigation system) to be fault-free and then diagnosing the measuring sensor fault is generally adopted. Considering that the structure of the filter can’t detect and isolate the faults of the inertial navigation system, the performance of the MEMS inertial navigation system declines due to complex environments resulting from vibrations and temperature changes; additionally, external interference may lead to the direct failure of the MEMS inertial device. Therefore, this paper studies a fault-tolerant navigation method based on a no-reference system. For the sensor sub-system of a custom micro air vehicle (MAV), a fault detection method based on a reference-free system is proposed. Based on the fault type analysis, some improvements have been made to the existing residual chi-square detection method, and an interactive residual fault detection method with distributed states is proposed. On this basis, aiming at the characteristics of a reference-free system, the weight distribution scheme of the reference system and the tested systems are studied, and a self-regulation filter fusion and fault detection method based on reference-free system is designed.


2011 ◽  
Vol 17 (11) ◽  
pp. 1106-1116 ◽  
Author(s):  
Cheon-Joong Kim ◽  
Ki-Jeong Yoo ◽  
Hyeon-Suk Kim ◽  
Joon Lyou




2011 ◽  
Vol 179-180 ◽  
pp. 1242-1247 ◽  
Author(s):  
Yu Rong Lin ◽  
Si Yan Guo ◽  
Guang Ying Zhang

A fault detection method applied to a redundant strapdown inertial navigation system, which usually undergoes rapid maneuvers, is developed in this paper. First, an improved four-points detection scheme that can significantly reduce the probability of false alarm of the generalized likelihood test(GLT) is present. Then, based on analyzing influences on the fault detection performance caused by the misalignment and scale fator errors and the random bias of a gyroscope, a parity vector error model is constructed and sequently the Kalman filtering scheme to compensate the parity vector error is designed. By example of a redundant measurement unit with four single-freedom-degree gyros, the fault detection method has been analyzed qualitatively and quantitatively through simulation tests. Simulation results demonstrate the favorable performance of the method.



2018 ◽  
Vol 71 (6) ◽  
pp. 1553-1566
Author(s):  
Jiazhen Lu ◽  
Lili Xie

This paper proposes a dynamic aided inertial navigation method to improve the attitude accuracy for ocean vehicles. The proposed method includes a dynamic identification algorithm and the utilisation of dynamic constraints to derive additional observations. The derived additional observations are used to update the filters and limit the attitude error based on the dynamic knowledge. In this paper, two dynamic conditions, constant speed cruise and quasi-static, are identified and corresponding additional velocity and position observations are derived. Simulation and experimental results show that the proposed method can improve and guarantee the accuracy of the attitude. The method can be used as a backup method to bridge external information outages or unavailability. Both the features of independence of external support and integrity of the Inertial Navigation System (INS) are enhanced.



2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875516 ◽  
Author(s):  
Elena Pivarčiová ◽  
Pavol Božek ◽  
Yuri Turygin ◽  
Ivan Zajačko ◽  
Aleksey Shchenyatsky ◽  
...  

The article deals with the research of the supplementation of industrial robot effector trajectory’s control systems by an inertial navigation system. The method of reverse validation and location of an object in a navigated reference system does not require additional calibration. The goal of the research is to verify the assumption that it is possible to control and correct the programmed mobile robot trajectory by implementing an inertial navigation system even in a case when the inertial navigation system is used as the only trajectory control device. The data obtained are processed by the proposed and detailed application.



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.



2018 ◽  
Vol 7 (2.7) ◽  
pp. 642
Author(s):  
V Appala Raju ◽  
P Vasundhara ◽  
V ChandraKanth Reddy ◽  
A Sai Aiswarya

This paper deals with the methods performing state estimation .that is position and orientation of Unmanned Arial Vehicle (UAV) using GPS, gyro, accelerometers and magnetometer sensors. Various methods are designed for position and orientation measurements of UAV. In this paper we proposed extended kalman filter based inertial navigation system using quaternions and 3D magnetometer. Initially we load UAV truth data from a file ,generate noisy UAV sensor measurements and perform UAV state estimation and display UAV state estimate results with proposed method compares with previously exited method extended  kalman filter based altitude and heading reference system using quaternion and 3D magnetometer simulation .Results shows that EKF-INS method gives better position and orientation of UAV.  



Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3083
Author(s):  
Donghui Lyu ◽  
Jiongqi Wang ◽  
Zhangming He ◽  
Yuyun Chen ◽  
Bowen Hou

As a new information provider of autonomous navigation, the on-orbit landmark observation offers a new means to improve the accuracy of autonomous positioning and attitude determination. A novel autonomous navigation method based on the landmark observation and the inertial system is designed to achieve the high-accuracy estimation of the missile platform state. In the proposed method, the navigation scheme is constructed first. The implicit observation equation about the deviation of the inertial system output is derived and the Kalman filter is applied to estimate the missile platform state. Moreover, the physical observability of the landmark and the mathematical observability of the navigation system are analyzed. Finally, advantages of the proposed autonomous navigation method are demonstrated through simulations compared with the traditional celestial-inertial navigation system and the deeply integrated celestial-inertial navigation system.



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