A fault-tolerant integrated navigation for UAV systems using time-variant vector distribution coefficients

2014 ◽  
Author(s):  
Yueqian Liang ◽  
Yingmin Jia ◽  
Fumitoshi Matsuno
Keyword(s):  
Fault Tolerant ◽  
Distribution Coefficients ◽  
Integrated Navigation ◽  
Vector Distribution

New fault-tolerant federated Kalman filters for integrated navigation

2018 ◽  
Vol 90 (1) ◽  
pp. 65-73
Author(s):  
Yueqian Liang ◽  
Yingmin Jia
Keyword(s):  
Kalman Filter ◽  
Kalman Filters ◽  
Fault Tolerant ◽  
Distribution Coefficients ◽  
Integrated Navigation ◽  
Content Type ◽  
Vector Distribution ◽  
Federated Kalman Filter ◽  
Aerial Vehicle ◽  
Navigation Accuracy

Purpose The purpose of this paper is to achieve accurate integrated navigation results for the unmanned aerial vehicle (UAV) systems even in the presence of possible navigation faults in the subsystems of the federated Kalman filter. Design/methodology/approach The federated Kalman filter is modified from two aspects to get accurate navigation results under abnormity. First, time-variant vector distribution coefficients trading off the navigation accuracy and the observability degree of each state component are computed to replace the traditional scalar coefficients. Second, a fault-tolerant filter is proposed as the local navigation filter. Findings Simulations for the navigation of a UAV system show that the proposed method can be applied for accurate navigation purpose even in the presence of subsystem navigation faults. Originality/value New fault-tolerant federated Kalman filters for integrated navigation are presented to achieve accurate navigation solutions.

Fault Tolerant Multi-Sensor Federated Filter for AUV Integrated Navigation

2019 ◽  
Author(s):  
Shuai Guo ◽  
Bo He ◽  
Chen Feng ◽  
Hanmin Liu ◽  
Feng Yin ◽  
...  
Keyword(s):  
Fault Tolerant ◽  
Integrated Navigation

scholarly journals A SINS/BDS Integrated Navigation Method Based on Classified Weighted Adaptive Filtering

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Xuchao Kang ◽  
Guangjun He ◽  
Xingge Li
Keyword(s):  
Adaptive Filtering ◽  
Navigation System ◽  
Fault Tolerant ◽  
Hypothesis Test ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Covariance Matching ◽  
Uncertain Model ◽  
Navigation Accuracy ◽  
Navigation Method

Aiming at the problem that the accuracy and stability of SINS/BDS integrated navigation system decrease due to uncertain model and observation anomalies, a SINS/BDS integrated navigation method based on classified weighted adaptive filtering is proposed. Firstly, the innovation covariance matching technology is used to detect whether there is any abnormality in the system as a whole. Then the types of anomalies are distinguished by hypothesis test. Different types of anomalies have different effects on state estimation. Based on the dynamic changes of innovation, different adaptive weighting methods are adopted to correct navigation information. The simulation results show that this method can effectively improve the fault-tolerant performance of integrated navigation system in complex environment with unknown anomaly types. When both model anomalies and observation anomalies exist, the speed and position accuracy are increased by 42% and 24% compared with the standard KF, 38% and 22% compared with the innovation orthogonal adaptive filtering, which has higher navigation accuracy.

scholarly journals A Fault-Tolerant Filtering Algorithm for SINS/DVL/MCP Integrated Navigation System

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaosu Xu ◽  
Peijuan Li ◽  
Jian-juan Liu
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Fault Tolerant ◽  
Doppler Velocity ◽  
Observation Data ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Data Set ◽  
Integrated Navigation System ◽  
Short Period

The Kalman filter (KF), which recursively generates a relatively optimal estimate of underlying system state based upon a series of observed measurements, has been widely used in integrated navigation system. Due to its dependence on the accuracy of system model and reliability of observation data, the precision of KF will degrade or even diverge, when using inaccurate model or trustless data set. In this paper, a fault-tolerant adaptive Kalman filter (FTAKF) algorithm for the integrated navigation system composed of a strapdown inertial navigation system (SINS), a Doppler velocity log (DVL), and a magnetic compass (MCP) is proposed. The evolutionary artificial neural networks (EANN) are used in self-learning and training of the intelligent data fusion algorithm. The proposed algorithm can significantly outperform the traditional KF in providing estimation continuously with higher accuracy and smoothing the KF outputs when observation data are inaccurate or unavailable for a short period. The experiments of the prototype verify the effectiveness of the proposed method.

scholarly journals Navigation Switching Strategy-Based SINS/GPS/ADS/DVL Fault-Tolerant Integrated Navigation System

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Weiqi Li ◽  
Rui Zhang ◽  
Hongjie Lei
Keyword(s):  
Data Processing ◽  
Navigation System ◽  
Fault Tolerant ◽  
Integrated Navigation ◽  
Sensor Faults ◽  
Sensor Failure ◽  
Switching Strategy ◽  
Integrated Navigation System ◽  
Serial Data ◽  
Federated Filtering

Considering the conventional federated filtering-based fault-tolerant integrated navigation system is difficult to be implemented by serial data processing circuits, this paper presents navigation switching strategy-based SINS/GPS/ADS/DVL fault-tolerant integrated navigation system to guarantee the reliability of integrated navigation system under sensor faults. When sensor failure appears, SINS and fault-free sensors are selected successively to form an integrated navigation system, such that reliable navigation parameters can be obtained. The simulation tests are implemented to verify that the SINS/GPS/ADS/DVL integrated navigation system can provide reliable navigation parameters when ADS and DVL are disabled.

Sign in / Sign up

Export Citation Format

Share Document