Calibration of in-run drifts of strapdown inertial Navigation system with uniaxial modulation rotation of Measurement unit.

2017 ◽  
Vol 25 (2) ◽  
pp. 3-17 ◽  
Author(s):  
G.I. Emel’yantsev ◽  
◽  
A.P. Stepanov ◽  
B.A. Blazhnov ◽  
◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Measurement Unit ◽  
Strapdown Inertial Navigation

Fault Detection Method Applied to a Redundant Strapdown Inertial Navigation System

2011 ◽  
Vol 179-180 ◽  
pp. 1242-1247 ◽  
Author(s):  
Yu Rong Lin ◽  
Si Yan Guo ◽  
Guang Ying Zhang
Keyword(s):  
Fault Detection ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Detection Method ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Measurement Unit ◽  
Detection Scheme ◽  
Vector Error ◽  
Strapdown Inertial Navigation

A fault detection method applied to a redundant strapdown inertial navigation system, which usually undergoes rapid maneuvers, is developed in this paper. First, an improved four-points detection scheme that can significantly reduce the probability of false alarm of the generalized likelihood test(GLT) is present. Then, based on analyzing influences on the fault detection performance caused by the misalignment and scale fator errors and the random bias of a gyroscope, a parity vector error model is constructed and sequently the Kalman filtering scheme to compensate the parity vector error is designed. By example of a redundant measurement unit with four single-freedom-degree gyros, the fault detection method has been analyzed qualitatively and quantitatively through simulation tests. Simulation results demonstrate the favorable performance of the method.

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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