INS/CNS/GNSS Integrated Navigation Method

2015 ◽  
pp. 279-305 ◽  
Author(s):  
Wei Quan ◽  
Xiaolin Gong ◽  
Jiancheng Fang ◽  
Jianli Li
Keyword(s):  
Integrated Navigation ◽  
Navigation Method

SINS/Odometer/Doppler Radar High-precision Integrated Navigation Method for Land Vehicle

2021 ◽  
pp. 1-1
Author(s):  
Bo Yang ◽  
Liang Xue ◽  
Hongdong Fan ◽  
Xiaogang Yanga
Keyword(s):  
High Precision ◽  
Doppler Radar ◽  
Integrated Navigation ◽  
Land Vehicle ◽  
Navigation Method

Study for Real-Time Ability of INS/CNS/GNSS Integrated Navigation Method

2015 ◽  
pp. 307-329 ◽  
Author(s):  
Wei Quan ◽  
Xiaolin Gong ◽  
Jiancheng Fang ◽  
Jianli Li
Keyword(s):  
Real Time ◽  
Integrated Navigation ◽  
Navigation Method

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.

Research on Seamless INS/GPS Integrated Navigation Algorithm

2011 ◽  
Vol 299-300 ◽  
pp. 1178-1181
Author(s):  
Tian Lai Xu ◽  
Yang Tian
Keyword(s):  
Neural Network ◽  
Estimation Accuracy ◽  
Gps Data ◽  
Positioning Error ◽  
Integrated Navigation ◽  
Adaptive Kalman Filter ◽  
Integrated Navigation System ◽  
Navigation Algorithm ◽  
Dynamical Error ◽  
Navigation Method

This paper proposed and discussed an INS/GPS integrated navigation method based on radial basis function neural network (RBFNN) to fuse INS and GPS data. When GPS signals were available, an adaptive Kalman filter was used to improve the estimation accuracy of INS errors, and then the RBFNN structure was trained to mimic the dynamical error model of INS. If GPS signals were unavailable, the trained RBFNN structure was utilized to bridge the GPS outages to achieve seamless navigation. Simulations in INS/GPS integrated navigation system showed the proposed method can reduce the positioning error during GPS outages.

High-precision SCNS/SINS integrated navigation method for shipboard

2016 ◽  
Author(s):  
Ling-Feng Zhou ◽  
Wang-Yang Zhao ◽  
Xiao-Ming Zhao ◽  
Yuan-jin Qu ◽  
Song-Pu Yang
Keyword(s):  
High Precision ◽  
Integrated Navigation ◽  
Navigation Method
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