scholarly journals Error Analysis and Compensation of Gyrocompass Alignment for SINS on Moving Base

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Bo Xu ◽  
Yang Liu ◽  
Wei Shan ◽  
Yi Zhang ◽  
Guochen Wang
Keyword(s):  
Error Analysis ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Doppler Velocity ◽  
Test Results ◽  
Improved Method ◽  
Calculation Algorithm ◽  
System Parameters ◽  
Velocity Error ◽  
Moving Base

An improved method of gyrocompass alignment for strap-down inertial navigation system (SINS) on moving base assisted with Doppler velocity log (DVL) is proposed in this paper. After analyzing the classical gyrocompass alignment principle on static base, implementation of compass alignment on moving base is given in detail. Furthermore, based on analysis of velocity error, latitude error, and acceleration error on moving base, two improvements are introduced to ensure alignment accuracy and speed: (1) the system parameters are redesigned to decrease the acceleration interference and (2) a data repeated calculation algorithm is used in order to shorten the prolonged alignment time caused by changes in parameters. Simulation and test results indicate that the improved method can realize the alignment on moving base quickly and effectively.

scholarly journals An Improved Adaptive Kalman Filter for Underwater SINS/DVL System

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Di Wang ◽  
Xiaosu Xu ◽  
Lanhua Hou
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Test Results ◽  
Adaptive Kalman Filter ◽  
Main Challenge ◽  
Vehicle Test ◽  
Navigation Method

The main challenge of Strap-down Inertial Navigation System (SINS)/Doppler velocity log (DVL) navigation system is the external measurement noise. Although the Sage–Husa adaptive Kalman filter (SHAKF) has been introduced in the integrated navigation field, the precision and stability of the SHAKF are still the tricky problems to be overcome. The primary aim of this paper is to improve the precision and stability of underwater SINS/DVL system. To attain this, a SINS/DVL tightly integrated model is established, where beam measurements are used without transforming them to 3D velocity. The proposed improved SHAKF algorithm is based on variable sliding window estimation and fading filter. The simulations and vehicle test results demonstrate the effectiveness of the proposed underwater SINS/DVL tightly integrated navigation method based on the improved SHAKF. In addition, the position accuracy of the designed method outperforms that of the SHAKF method.

Study on ZUPT Technology Applied in SINS

2012 ◽  
Vol 546-547 ◽  
pp. 1360-1365
Author(s):  
Xing Xing Dai ◽  
Ling Xie ◽  
Yu Liang Mao ◽  
Chun Lei Song
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Error Control ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Velocity Error ◽  
Zero Velocity ◽  
Position Errors

Zero Velocity Update (ZUPT) is an essential method of error control in Stapdown Inertial Navigation System (SINS), which is extensively used because of its cheapness and efficiency. ZUPT uses the output of velocity error of SINS when the carrier is parking, to update the errors of other items in SINS. This method can improve the position and direction precisions of SINS. Kalman filter is chosen as the method of ZUPT to correct the velocity and position errors in SINS in this article. The method of ZUPT based on Kalman filter is applied to the vehicle experiment. The results of the vehicle experiment indicate that the ZUPT based on Kalman filter is efficient and powerful in error control, and the Kalman filter designed based on SINS is proper.

scholarly journals Analysis and Self-Calibration Method for Asynchrony between Sensors in Rotation INS

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2921 ◽  
Author(s):  
Jie Sui ◽  
Lei Wang ◽  
Tao Huang ◽  
Qi Zhou
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Velocity Error ◽  
Self Calibration ◽  
Axis Rotation ◽  
The Impact ◽  
Navigation Errors

The gyroscope, accelerometer and angular encoder are the most important components in a dual-axis rotation inertial navigation system (RINS). However, there are asynchronies among the sensors, which will thus lead to navigation errors. The impact of asynchrony between the gyroscope and angular encoder on the azimuth error and the impact of asynchrony between the gyroscope and accelerometer on the velocity error are analyzed in this paper. A self-calibration method based on navigation errors is proposed based on the analysis above. Experiments show that azimuth and velocity accuracy can be improved by compensating the asynchronies.

A Design of MIMU/GPS Integrated Navigation System

2013 ◽  
Vol 278-280 ◽  
pp. 1719-1722 ◽  
Author(s):  
Xiao Yu Zhang ◽  
Chun Lei Song
Keyword(s):  
Navigation System ◽  
Inertial Measurement Unit ◽  
High Performance ◽  
Inertial Navigation System ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Test Results ◽  
Simulation Test ◽  
Integrated Navigation System ◽  
Navigation Algorithm

A new scheme of small integrated navigation system based on micro inertial measurement unit (MIMU), global position system (GPS) is presented. The characteristic of these sensors and the structure of system are introduced respectively. The TI high performance floating point DSP TMS320C6713B is used as core processor, which is designed to realize both the data collecting and the navigation calculating. According to the error models of inertial navigation system, an integrated navigation algorithm used Kalman filter is proposed to fuse the information from all of the sensors. The simulation test results show the feasibility of the system design.

scholarly journals Improved Underwater Integrated Navigation System using Unscented Filtering Approach

2015 ◽  
Vol 69 (3) ◽  
pp. 561-581 ◽  
Author(s):  
Mohammad Shabani ◽  
Asghar Gholami
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Measurement Models ◽  
Error State ◽  
Filtering Approach

In underwater navigation, the conventional Error State Kalman Filter (ESKF) is used for combining navigation data where due to first order linearization of the nonlinear equations of the dynamics and measurements, considerable error is induced in estimated error state and covariance matrices. This paper presents an underwater integrated inertial navigation system using the unscented filter as an improved nonlinear version of the Kalman filter family. The designed system consists of a strap-down inertial navigation system accompanying Doppler velocity log and depth meter. In the proposed approach, to use the nonlinear capabilities of the unscented filtering approach the integrated navigation system is implemented in a direct approach where the nonlinear total state dynamic and and measurement models are utilised without any linearization. To our knowledge, no results have been reported in the literature on the experimental evaluation of the unscented-based integrated navigation system for underwater vehicles. The performance of the designed system is studied using real measurements. The results of the lake test show that the proposed system estimates the vehicle's position more accurately compared with the conventional ESKF structure.

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