Simulating Gyro of Strapdown Inertial Navigation System Based on Star Sensor

2012 ◽  
Vol 182-183 ◽  
pp. 1090-1094
Author(s):  
Wei Gao ◽  
Lei Zhang
Keyword(s):  
Angular Velocity ◽  
Real Time ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Star Sensor ◽  
Measuring Instrument ◽  
Priori Information ◽  
Strapdown Inertial Navigation

In inertial navigation system, gyro is used to measure the angular velocity of carrier relative to inertial space for achieve attitude matrix updated in real time. Gyro difficult to eliminate the error, results in strapdown inertial navigation system precision decrease with time. Star sensor is a high-precision attitude measuring instrument and don’t require any priori information, the attitude date can be provided by star sensor. Thus, gyro is simulated by star sensor in order to improve the precision of strapdown inertial navigation system.

Estimating Gyro Drift of Strapdown Inertial Navigation System Based on Star Sensor

2012 ◽  
Vol 566 ◽  
pp. 235-238
Author(s):  
Guang Tao Zhou ◽  
Gui Min Shi ◽  
Lei Zhang ◽  
Kai Li
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Model Simulation ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Star Sensor ◽  
Integrated Navigation ◽  
Working Principle ◽  
Gyro Drift ◽  
Strapdown Inertial Navigation

In the strapdown inertial navigation system (SINS), gyro drift will result in navigation errors. A new algorithm based on star sensor is proposed in this paper to estimate gyro drift. The paper analyzed the working principle of star sensor and the technique of estimating gyro drift. Gyro drift can be estimated through the high-precision attitude information provided by a star sensor. Kalman filter is used in the integrated navigation model. Simulation results show that the proposed algorithm can estimate gyro drift accurately and improve the precision of SINS.

scholarly journals Attitude Output of Strapdown Inertial Navigation System Based on Laser Gyro

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Real Time ◽  
Navigation System ◽  
High Speed ◽  
Data Exchange ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Data Communication ◽  
Data Access ◽  
Strapdown Inertial Navigation System ◽  
Strapdown Inertial Navigation

Aiming at the real-time problems of signal acquisition, attitude calculation and data exchange of strapdown inertial navigation system, the data exchange between the core device of three-axis screw instrument and three-axis accelerometer sensor inertial unit (IMU) is analyzed. The RS-232 serial interface and can bus interface are adopted, which can not meet the requirements of high-speed sampling and real-time data transmission of each sensor. A new method based on FPGA dual port RAM and dual DSP is proposed Speed data access mode, through the main control CPU clock synchronization, can effectively solve the bottleneck problem of data communication between IMU attitude data and core equipment, and realize the rapid response ability of vehicle navigation system. Experiments and simulations show that the highest frequency attitude update rate of the method can reach 2000kHz, which can effectively solve the input and output data and navigation calculation ability, and improve the maneuverability of the carrier.

scholarly journals Analysis of the Strapdown Inertial Navigation System (SINS) Error Genesis

2018 ◽  
Vol 6 (1) ◽  
pp. 44-54
Author(s):  
Pjotrs Trifonovs-Bogdanovs ◽  
Anvar Zabirov
Keyword(s):  
Angular Velocity ◽  
Navigation System ◽  
Velocity Measurement ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Critical Element ◽  
Velocity Sensor ◽  
Strapdown Inertial Navigation

Abstract Analysis and simulation of the Strapdown Inertial Navigation System (SINS) error genesis revealed that the East Feedback Contour has the greatest influence on the development of an error in this model, and angular velocity sensor Δω𝒚 is the critical element. In order to prevent the development of an error, structural correction in the East Feedback Contour, and elements that are more critical, namely in angular velocity measurement sensors is the best option.

Research and Simulation on the Algorithm of Guided Projectile Strapdown Inertial Navigation System

2012 ◽  
Vol 433-440 ◽  
pp. 3746-3752 ◽  
Author(s):  
Jian Hui Tian ◽  
Jia Sheng Zhao ◽  
Yan Cao ◽  
Wei Wang ◽  
Wei Xu ◽  
...  
Keyword(s):  
Real Time ◽  
Relative Error ◽  
Navigation System ◽  
Short Range ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Rotation Vector ◽  
Damage Probability ◽  
Strapdown Inertial Navigation

To improve the hit probability and damage probability of guided projectile, made the strapdown inertial navigation technology better application in guided projectile, based on the feature of short range and short flying time of guided projectile, a simplification model of SINS (strapdown inertial navigation system) was proposed. The optimal 3-subsample rotation vector simulation platform was founded based on the tradition method, and this system was also checked by simulation using three-channel databases from simulator testing. The results show that this system not only can satisfy the requirement of real-time and precision, but also can improve the relative error to 10-6. The influence of direction draft to the guided projectile is also reduced.

Observability and Estimation Error Analysis of the Initial Fine Alignment Filter for Nonleveling Strapdown Inertial Navigation System

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Seong Yun Cho ◽  
Hyung Keun Lee ◽  
Hung Kyu Lee
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
The State ◽  
State Model ◽  
Low Grade ◽  
State Variables ◽  
Estimation Errors ◽  
Strapdown Inertial Navigation

In this paper, performance of the initial fine alignment for the stationary nonleveling strapdown inertial navigation system (SDINS) containing low-grade gyros is analyzed. First, the observability is analyzed by conducting a rank test of an observability matrix and by investigating the normalized error covariance of the extended Kalman filter based on the ten-state model. The results show that the accelerometer biases on horizontal axes are unobservable. Second, the steady-state estimation errors of the state variables are derived using the observability equation. It is verified that the estimates of the state variables have errors due to the unobservable state variables and nonleveling attitude angles of a vehicle containing the SDINS. Especially, this paper shows that the larger the attitude angles of the vehicle are, the greater the estimation errors are. Finally, it is shown that the performance of the eight-state model excluding the two unobservable state variables is better than that of the ten-state model in the fine alignment by a Monte Carlo simulation.

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