scholarly journals Robust adaptive filtering method for SINS/SAR integrated navigation system

2011 ◽  
Vol 15 (6) ◽  
pp. 425-430 ◽  
Author(s):  
Shesheng Gao ◽  
Yongmin Zhong ◽  
Wei Li
Keyword(s):  
Adaptive Filtering ◽  
Navigation System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Filtering Method ◽  
Robust Adaptive

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.

Application of Federated Filter to AUV Based on Terrain-Aided SINS

2014 ◽  
Vol 711 ◽  
pp. 338-341 ◽  
Author(s):  
Qi Wang ◽  
Cheng Shan Qian ◽  
Zi Jia Zhang ◽  
Chang Song Yang
Keyword(s):  
Kalman Filtering ◽  
Navigation System ◽  
Autonomous Underwater Vehicles ◽  
Inertial Navigation ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Filtering Method ◽  
Long Time ◽  
Federated Filtering ◽  
Strapdown Inertial Navigation

To improve the navigation precision and reliability of autonomous underwater vehicles, a terrain-aided strapdown inertial navigation based on Federated Filter (FF) is proposed in this paper. The characteristics of strapdown inertial navigation system and terrain-aided navigation system are described in this paper, and Federated Filtering method is applied to the information fusion. Simulation experiments of novel integrated navigation system proposed in the paper were carried out comparing to the traditional Kalman filtering methods. The experiment results suggest that the Federated Filtering method is able to improve the long-time navigation precision and reliability, relative to the traditional Kalman Filtering method.

Application of Fuzzy Adaptive Kalman Filtering on GPS/INS Integrated Navigation System

2011 ◽  
Vol 317-319 ◽  
pp. 1512-1517
Author(s):  
Ming Wei Liu ◽  
Fen Fen Xiong ◽  
Jin Huang
Keyword(s):  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Navigation System ◽  
Adaptive Controller ◽  
Integrated Navigation ◽  
Noise Levels ◽  
Integrated Navigation System ◽  
Navigation Algorithm ◽  
The Common ◽  
Fuzzy Adaptive

A fuzzy adaptive Kalman filtering navigation algorithm is proposed and further applied to the GPS/INS integrated navigation system in this paper. The common Sage-Husa adaptive filtering algorithm and its drawbacks are elaborated. In order to adjust the Sage-Husa adaptive filter to the optimal state to improve the accuracy of the integrated navigation system, the fuzzy logic adaptive controller is used to adjust the weighting form for the covariance matrix of measurement noise to gradually make it approach to the true noise levels. Simulation results show that the proposed algorithm can not only inhibit the filtering divergence but also improve filtering accuracy.

scholarly journals A Quaternion-Based Robust Adaptive Spherical Simplex Unscented Particle Filter for MINS/VNS/GNS Integrated Navigation System

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Ke Jia ◽  
Yifei Pei ◽  
Zhaohui Gao ◽  
Yongmin Zhong ◽  
Shesheng Gao ◽  
...  
Keyword(s):  
Particle Filter ◽  
Navigation System ◽  
Unscented Kalman Filter ◽  
Model Simulation ◽  
Adaptive Estimation ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Unscented Particle Filter ◽  
Spherical Simplex ◽  
Robust Adaptive

An improved filtering algorithm-robust adaptive spherical simplex unscented particle filter (RASSUPF) is proposed to achieve high accuracy, induce the amount of computation, and resist the influence of abnormal interference for the MINS/VNS/GNS integrated navigation system. This algorithm adopts spherical simplex unscented transformation (SSUT) to approximate the probability distribution, employs the spherical simplex unscented Kalman filter (SSUKF) to generate the importance sampling density of particle filter, and applies robust and adaptive estimation to control the influence of the abnormal information on the state model and the observation model. Simulation results demonstrate the proposed algorithm can effectively reduce the navigation error, improve the navigation positioning precision, and decrease the computation cost.

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