scholarly journals In-Flight Alignment UsingH∞Filter for Strapdown INS on Aircraft

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Fu-Jun Pei ◽  
Xuan Liu ◽  
Li Zhu
Keyword(s):  
Inertial Navigation System ◽  
Inertial Frame ◽  
Alignment Error ◽  
System State ◽  
Alignment Method ◽  
Initial Alignment ◽  
Dynamic Disturbance ◽  
Aircraft Flight ◽  
Value Decomposition ◽  
Constant System

In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then aH∞filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition.

scholarly journals Parameter Identification Method for SINS Initial Alignment under Inertial Frame

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Haijian Xue ◽  
Xiaosong Guo ◽  
Zhaofa Zhou
Keyword(s):  
Parameter Identification ◽  
Inertial Frame ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Initial Alignment ◽  
Dynamic Disturbance ◽  
Identification Method ◽  
Reference Information ◽  
External Reference ◽  
Alignment Model

The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. The conventional alignment method with parameter identification has been already applied widely, but it needs to calculate the gyroscope drifts through two-position method; then the time of initial alignment is greatly prolonged. For this issue, a novel self-alignment algorithm by parameter identification method under inertial frame for SINS is proposed in this paper. Firstly, this coarse alignment method using the gravity in the inertial frame as a reference is discussed to overcome the limit of dynamic disturbance on a rocking base and fulfill the requirement for the fine alignment. Secondly, the fine alignment method by parameter identification under inertial frame is formulated. The theoretical analysis results show that the fine alignment model is fully self-aligned with no external reference information and the gyrodrifts can be estimated in real time. The simulation results demonstrate that the proposed method can achieve rapid and highly accurate initial alignment for SINS.

scholarly journals Initial Self-Alignment for Marine Rotary SINS Using Novel Adaptive Kalman Filter

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Fujun Pei ◽  
Li Zhu ◽  
Jian Zhao
Keyword(s):  
Kalman Filter ◽  
Inertial Frame ◽  
Error Model ◽  
Alignment Method ◽  
Initial Alignment ◽  
Adaptive Kalman Filter ◽  
Dynamic Disturbance ◽  
System Error ◽  
Angular Velocities ◽  
Initial Attitude

The accurate initial attitude is essential to affect the navigation result of Rotary Strapdown Inertial Navigation System (SINS), which is usually calculated by initial alignment. But marine mooring Rotary SINS has to withstand dynamic disturbance, such as the interference angular velocities and accelerations caused by surge and sway. In order to overcome the limit of dynamic disturbance under the marine mooring condition, an alignment method using novel adaptive Kalman filter for marine mooring Rotary SINS is developed in this paper. This alignment method using the gravity in the inertial frame as a reference is discussed to deal with the lineal and angular disturbances. Secondly, the system error model for fine alignment in the inertial frame as a reference is established. Thirdly, PWCS and SVD are used to analyze the observability of the system error model for fine alignment. Finally, a novel adaptive Kalman filter with measurement residual to estimate measurement noise variance is designed. The simulation results demonstrate that the proposed method can achieve better accuracy and stability for marine Rotary SINS.

An Improved Initial Alignment Method of Strap-Down Inertial Navigation System on a Swaying Base

2013 ◽  
Vol 415 ◽  
pp. 143-148
Author(s):  
Li Hua Zhu ◽  
Xiang Hong Cheng
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Initial Alignment ◽  
Vehicle Simulation ◽  
Robust Property ◽  
Simulation Results ◽  
Lever Arm Effect ◽  
The Impact

The design of an improved alignment method of SINS on a swaying base is presented in this paper. FIR filter is taken to decrease the impact caused by the lever arm effect. And the system also encompasses the online estimation of gyroscopes’ drift with Kalman filter in order to do the compensation, and the inertial freezing alignment algorithm which helps to resolve the attitude matrix with respect to its fast and robust property to provide the mathematical platform for the vehicle. Simulation results show that the proposed method is efficient for the initial alignment of the swaying base navigation system.

An initial alignment method for strapdown gyrocompass based on gravitational apparent motion in inertial frame

Measurement ◽  
2014 ◽  
Vol 55 ◽  
pp. 593-604 ◽  
Author(s):  
Xixiang Liu ◽  
Xiaosu Xu ◽  
Yu Zhao ◽  
Lihui Wang ◽  
Yiting Liu
Keyword(s):  
Apparent Motion ◽  
Inertial Frame ◽  
Alignment Method ◽  
Initial Alignment

scholarly journals A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xixiang Liu ◽  
Xiaosu Xu ◽  
Yiting Liu ◽  
Lihui Wang
Keyword(s):  
Kalman Filter ◽  
Covariance Matrix ◽  
Nonlinear Problem ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Error Model ◽  
The State ◽  
Alignment Method ◽  
Initial Alignment ◽  
Alignment Process

In the initial alignment process of strapdown inertial navigation system (SINS), large initial misalignment angles always bring nonlinear problem, which causes alignment failure when the classical linear error model and standard Kalman filter are used. In this paper, the problem of large misalignment angles in SINS initial alignment is investigated, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process. According to the analysis, an alignment method for SINS based on multiresetting the state covariance matrix of Kalman filter is designed to deal with large initial misalignment angles, in which classical linear error model and standard Kalman filter are used, but the state covariance matrix should be multireset before the steady process until large misalignment angles are decreased to small ones. The performance of the proposed method is evaluated by simulation and car test, and the results indicate that the proposed method can fulfill initial alignment with large misalignment angles effectively and the alignment accuracy of the proposed method is as precise as that of alignment with small misalignment angles.

Fast Fine Initial Self-alignment of INS in Erecting Process on Stationary Base

2017 ◽  
Vol 71 (3) ◽  
pp. 697-710 ◽  
Author(s):  
Jianli Li ◽  
Yiqi Li ◽  
Baiqi Liuxs
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Euler Angle ◽  
Alignment Method ◽  
State Variables ◽  
Initial Alignment ◽  
Angle Error ◽  
Alignment Model ◽  
System Observability

Fine initial alignment is vital to the Inertial Navigation System (INS) before the launching of a missile. The existing initial alignment methods are mainly performed on a stationary base after the missile has been erected to the vertical state. However, these methods consume extra alignment time and some state variables have poor degrees of observability, thus losing the rapidity of alignment. In order to solve the problem, a fast fine initial self-alignment method of a missile-borne INS is proposed, which is performed during the erecting process on a stationary base. The convected Euler angle error is modelled to optimise the erecting manoeuvre which can prevent large Euler angle errors and improve the system observability. The fine initial alignment model is established to estimate and correct the initial misalignment. Several experiments verify that the proposed method is effective for improving the rapidity of the fine initial alignment for a missile-borne INS.

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