scholarly journals Study on Transfer Alignment Stable Targeting Method of Moving Base Based on Velocity Plus Attitude Matching Algorithm

2015 ◽  
Author(s):  
Zhen Wang ◽  
Min Gao ◽  
Fengqi Gao ◽  
Weiwei Gao
Keyword(s):  
Matching Algorithm ◽  
Transfer Alignment ◽  
Moving Base

Analysis of Three Velocity Plus Attitude Matching Methods for Transfer Alignment

2012 ◽  
Vol 433-440 ◽  
pp. 2802-2807
Author(s):  
Ying Hong Han ◽  
Wan Chun Chen
Keyword(s):  
Kalman Filter ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Misalignment Angle ◽  
Inertial Navigation Systems ◽  
Excellent Performance ◽  
Transfer Alignment ◽  
Matching Methods ◽  
Moving Base

For inertial navigation systems (INS) on moving base, transfer alignment is widely applied to initialize it. Three velocity plus attitude matching methods are compared. And Kalman filter is employed to evaluate the misalignment angle. Simulations under the same conditions show which scheme has excellent performance in precision and rapidness of estimations.

scholarly journals An Improved Adaptive Compensation H∞ Filtering Method for the SINS’ Transfer Alignment Under a Complex Dynamic Environment

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 401 ◽  
Author(s):  
Weiwei Lyu ◽  
Xianghong Cheng ◽  
Jinling Wang
Keyword(s):  
Inertial Sensors ◽  
Dynamic Environment ◽  
Inertial Navigation ◽  
Adaptive Compensation ◽  
Complex Dynamic ◽  
Transfer Alignment ◽  
Filtering Method ◽  
Balance Accuracy ◽  
Alignment System ◽  
Moving Base

Transfer alignment on a moving base under a complex dynamic environment is one of the toughest challenges in a strapdown inertial navigation system (SINS). With the aim of improving rapidity and accuracy, velocity plus attitude matching is applied in the transfer alignment model. Meanwhile, the error compensation model is established to calibrate and compensate the errors of inertial sensors online. To suppress the filtering divergence during the process of transfer alignment, this paper proposes an improved adaptive compensation H∞ filtering method. The cause of filtering divergence has been analyzed carefully and the corresponding adjustment and optimization have been made in the proposed adaptive compensation H∞ filter. In order to balance accuracy and robustness of the transfer alignment system, the robustness factor of the adaptive compensation H∞ filter can be dynamically adjusted according to the complex external environment. The aerial transfer alignment experiments illustrate that the adaptive compensation H∞ filter can effectively improve the transfer alignment accuracy and the pure inertial navigation accuracy under a complex dynamic environment, which verifies the advantage of the proposed method.

Transfer Alignment for Space Vehicles Launched from a Moving Base

2005 ◽  
Vol 55 (3) ◽  
pp. 245-252 ◽  
Author(s):  
S. K. Chaudhuri ◽  
P. K. Nandi
Keyword(s):  
Space Vehicles ◽  
Transfer Alignment ◽  
Moving Base

Attitude Matching for Gimbaled Inertial Navigation System Transfer Alignment

2012 ◽  
Vol 190-191 ◽  
pp. 768-773
Author(s):  
Zhi Jian Ding ◽  
Hong Cai ◽  
Hua Bo Yang ◽  
Yuan Cao
Keyword(s):  
Kalman Filter ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Misalignment Angle ◽  
Inertial Navigation Systems ◽  
Angle Error ◽  
Transfer Alignment ◽  
Moving Base ◽  
Alignment Model

Abstract: Aiming at transfer alignment of gimbaled INS(Inertial Navigation Systems) on moving base, the paper proposes an attitude matching alignment model to calibrate the slave platform. This method is achieved by applying a Kalman filter, which based on the frame angle error equations, to estimate the fixed misalignment angle and obtain the misalignment angle. Firstly, the frame dynamics equations are introduced and the relation between the fixed angle and misalignment angle is discussed. Secondly, the frame angular error differential equations are built up via the frame angle information from the master and the slave INS platform. Lastly, the attitude matching alignment model is designed based on Kalman filter technology. The simulation results show that the proposed method can obtain an alignment accuracy of 40", and the corresponding alignment time is 30 seconds.

Design of Transfer Alignment for Micro-Inertial Attitude Measurement System Based on Distributed

2015 ◽  
Vol 789-790 ◽  
pp. 896-900
Author(s):  
Yu Kun Wang ◽  
Song Han ◽  
Zhuang Hua Liu ◽  
Xiang Hai Yu
Keyword(s):  
Measurement System ◽  
Engineering Application ◽  
Attitude Measurement ◽  
Measurement Equation ◽  
Matching Algorithm ◽  
Transfer Alignment ◽  
Attitude Error ◽  
Aerial Vehicle ◽  
Vehicle Test ◽  
Set Up

In view of the specific environment of the reconnaissance UAV (Unmanned Aerial Vehicle), it is necessary to design a micro-inertial attitude measurement system. The ground-demo of the distributed micro-inertial attitude measurement system was set up. Then the attitude error measurement equation was deduced. Based on this, the Kalman filter using the “velocity and attitude” matching algorithm was designed. Through vehicle test, the experimental results show that the precisions of horizontal angle and azimuth angle are superior to 1.5′ and 2.3′ respectively by the proposed algorithm. All these characteristics show that the scheme is feasible and can provide reference for the engineering application of the distributed micro-inertial attitude measurement system.

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