Application of Modified Ellipsoidal Filter in Integrated Strapdown Inertial Navigation System

2018 ◽  
Vol 50 (4) ◽  
pp. 35-53
Author(s):  
Nikolay N. Salnikov ◽  
Vyacheslav F. Gubarev ◽  
Sergey V. Melnichuk
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Strapdown Inertial Navigation

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.

Application of Intelligent Materials in Vibration Control for Strapdown Inertial Navigation System

2013 ◽  
Vol 804 ◽  
pp. 275-278
Author(s):  
He Sun ◽  
Fan Li ◽  
Jian Hui Zhao
Keyword(s):  
Vibration Control ◽  
Navigation System ◽  
Pid Controller ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Control Methods ◽  
Intelligent Materials ◽  
Fuzzy Pid Controller ◽  
Strapdown Inertial Navigation

This paper investigated the vibration control based on intelligent materials for strapdown inertial navigation system (SINS) from theoretical analysis to simulation verification. At first, significance of vibration control in SINS and the disadvantages of the traditional vibration control methods were set forth. Then, intelligent material and structure were introduced to improve the situation. A method of combining active and passive vibration control based on piezoelectric ceramic had been put forward. Through modeling and designing PID and fuzzy PID controller separately, the simulation results show that both the model and the control methods are effective. Finally, its effectiveness and the further researched required to be done were summarized.

Analysis of the Symmetry for a Rotating Strapdown Inertial Navigation System

2012 ◽  
Vol 566 ◽  
pp. 703-706
Author(s):  
Wei Gao ◽  
Ya Zhang ◽  
Qian Sun ◽  
Yue Yang Ben
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Basic Requirement ◽  
Position Accuracy ◽  
Rotation Method ◽  
Constant Bias ◽  
Strapdown Inertial Navigation

It is known that the precision of the strapdown inertial navigation system is influenced by constant bias of inertial sensors. A method of self-compensation based on a rotating inertial navigation system is proposed to enhance the precision. The constant drift of gyro and accelerometers is modulated into a seasonal and zero-mean form. In the paper, the theory of the rotary modulation and the basic requirement of the rotation method are analyzed. A new dual-axis rotating method is put forward. Simulations have been done. And the results indicate that the method can clear up the constant bias of the inertial sensors quickly and effectively. The position accuracy can be greatly enhanced compared with no rotary manner.

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