Adaptive Kalman Filter for INS/GPS Integrated Navigation System

2013 ◽  
Vol 336-338 ◽  
pp. 332-335 ◽  
Author(s):  
Tian Lai Xu
Keyword(s):  
Kalman Filter ◽  
Global Positioning System ◽  
Navigation System ◽  
A Priori ◽  
Noise Characteristic ◽  
Integrated Navigation ◽  
Adaptive Kalman Filter ◽  
Integrated Navigation System ◽  
Global Positioning ◽  
Priori Information

Inertial Navigation System (INS) and Global Positioning System (GPS) are commonly integrated to overcomes each systems inadequacies and provide an accurate navigation solution. The integration of INS and GPS is usually achieved using a Kalman filter. The accuracy of INS/GPS deteriorates in condition that a priori information used in Kalman filter does not accord with the actual environmental conditions. To address this problem, an improved Sage-Husa filter is presented. In this method, the measurement noise characteristic is adjusted if and only if filtering abnormality exists, avoiding filter instability and reducing computational burden caused by adjusting noise characteristic too frequently in Sage-Husa filter. Simulations in INS/GPS integrated navigation showed improvement in positioning accuracy.

Seamless INS/GPS Integration Based on Support Vector Machines

2013 ◽  
Vol 336-338 ◽  
pp. 277-280 ◽  
Author(s):  
Tian Lai Xu
Keyword(s):  
Support Vector Machines ◽  
Global Positioning System ◽  
Navigation System ◽  
Superior Performance ◽  
Support Vector ◽  
Integrated Navigation ◽  
Positioning Accuracy ◽  
Integrated Navigation System ◽  
Vector Machines ◽  
Global Positioning

The combination of Inertial Navigation System (INS) and Global Positioning System (GPS) provides superior performance in comparison with either a stand-alone INS or GPS. However, the positioning accuracy of INS/GPS deteriorates with time in the absence of GPS signals. A least squares support vector machines (LS-SVM) regression algorithm is applied to INS/GPS integrated navigation system to bridge the GPS outages to achieve seamless navigation. In this method, LS-SVM is trained to model the errors of INS when GPS is available. Once the LS-SVM is properly trained in the training phase, its prediction can be used to correct the INS errors during GPS outages. Simulations in INS/GPS integrated navigation showed improvements in positioning accuracy when GPS outages occur.

scholarly journals Modified Sage-Husa Adaptive Kalman Filter-Based SINS/DVL Integrated Navigation System for AUV

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Ruixin Liu ◽  
Fucheng Liu ◽  
Chunning Liu ◽  
Pengchao Zhang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Autonomous Underwater Vehicle ◽  
Positive Definiteness ◽  
Integrated Navigation ◽  
Adaptive Kalman Filter ◽  
Integrated Navigation System ◽  
The Stability ◽  
Navigation Accuracy ◽  
Navigation Errors

This paper presents a modified Sage-Husa adaptive Kalman filter-based SINS/DVL integrated navigation system for the autonomous underwater vehicle (AUV), where DVL is employed to correct the navigation errors of SINS that accumulate over time. When negative definite items are large enough, different from the positive definiteness of noise matrices which cannot be guaranteed for the conventional Sage-Husa adaptive Kalman filter, the proposed modified Sage-Husa adaptive Kalman filter deletes the negative definite items of adaptive update laws of the noise matrix to ensure the convergence of the Sage-Husa adaptive Kalman filter. In other words, this method sacrifices some filtering precision to ensure the stability of the filter. The simulation tests are implemented to verify that expected navigation accuracy for AUV can be obtained using the proposed modified Sage-Husa adaptive Kalman filter.

Application of Fuzzy Adaptive Fusion Algorithm in INS/BNS/GPS Integrated Navigation System

2012 ◽  
Vol 232 ◽  
pp. 205-209
Author(s):  
Yan Ren ◽  
Duan Xu ◽  
Wei Feng Yue
Keyword(s):  
Data Fusion ◽  
Global Positioning System ◽  
Navigation System ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Integrated Navigation System ◽  
Global Positioning ◽  
Adaptive Fusion ◽  
Fuzzy Fusion ◽  
Fuzzy Adaptive

The problem of data fusion based on filter is studied for an integrated inertial navigation system / Beidou navigation system / global positioning system (INS/BNS/GPS) with uncertain noise and conditionality of using GPS. The integrated navigation system can be divided into two integrated navigation subsystems (INS/BNS and INS/GPS). The signals from GPS and BNS receivers are easy to be disturbed, so filter is used to estimate the subsystem errors which are transmitted to fusion center online. Then data fusion is carried out by using the fuzzy fusion algorithm. Simulation results show that the algorithm can improve the accuracy and stability of navigation system.

Multirate Adaptive Kalman Filter for Marine Integrated Navigation System

2016 ◽  
Vol 70 (3) ◽  
pp. 628-647 ◽  
Author(s):  
Narjes Davari ◽  
Asghar Gholami ◽  
Mohammad Shabani
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Dynamic Environment ◽  
Statistical Information ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Adaptive Kalman Filter ◽  
Integrated Navigation System ◽  
Imperfect Knowledge ◽  
Marine Navigation

In the conventional integrated navigation system, the statistical information of the process and measurement noises is considered constant. However, due to the changing dynamic environment and imperfect knowledge of the filter statistical information, the process and measurement covariance matrices are unknown and time-varying. In this paper, a multirate adaptive Kalman filter is proposed to improve the performance of the Error State Kalman Filter (ESKF) for a marine navigation system. The designed navigation system is composed of a strapdown inertial navigation system along with Doppler velocity log and inclinometer with different sampling rates. In the proposed filter, the conventional adaptive Kalman filter is modified by adaptively tuning the measurement covariance matrix of the auxiliary sensors that have varying sampling grates based on the innovation sequence. The performance of the proposed filter is evaluated using real measurements. Experimental results show that the average root mean square error of the position estimated by the proposed filter can be decreased by approximately 60% when compared to that of the ESKF.

Research on Integrated Navigation Algorithm Based on ANFIS

2011 ◽  
Vol 88-89 ◽  
pp. 438-441
Author(s):  
Tian Lai Xu ◽  
Yang Tian
Keyword(s):  
Global Positioning System ◽  
Navigation System ◽  
Fuzzy Inference ◽  
Integrated Navigation ◽  
Inference System ◽  
Integrated Navigation System ◽  
Navigation Algorithm ◽  
Neuro Fuzzy ◽  
Global Positioning ◽  
Navigation Method

Combination of Global Positioning System (GPS) and Inertial Navigation System (INS) can improve the navigation performance that is superior to either one. This paper proposed and discussed an INS/GPS integrated navigation method based on adaptive neuro-Fuzzy Inference System (ANFIS) to fuse INS and GPS data. In this method, an ANFIS network was trained to mimic the error dynamical model of INS when GPS signals were available. If GPS outages occur, the trained ANFIS network is utilized to bridge the GPS outages. Simulations in INS/GPS integrated navigation system show the proposed method can reduce the positioning error during GPS outages.

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