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Research and Application of GPS/INS Integrated Navigation and Nonlinear Filtering in Navigation System

Author: ZhengZuo
Tutor: HaoYingGuang
School: Dalian University of Technology
Course: Communication and Information System
Keywords: Integrated Navigation Kalman filter Initial alignment Gyro noise reduction
CLC: TN967.2
Type: Master's thesis
Year: 2010
Downloads: 461
Quote: 1
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Abstract


This article aims to improve the accuracy of inertial navigation , the research on the following aspects of the problem , including: The Research and Implementation of SINS integrated navigation system and global positioning system , gyro random drift estimates based on particle filter in applied research, based on large misalignment angle of INS initial alignment . The main research contents are as follows: 1, from the practical point of view , of micro-electromechanical systems ( MEMS ) gyro signal noise reduction . First, the gyro random drift signal preprocessing , create time-varying non- stationary conditions ARMA model ; gyro error signal using a particle filter can be applied to nonlinear systems based on its improved noise reduction Processing ; Allan variance analysis techniques of filtering results were analyzed for the identification of sources of error parameters . Experimental results show that the filtering and modeling methods can effectively reduce gyro random drift errors , to suppress the noise in the gyro signal , and its error estimation and compensation , to some extent, improved navigation accuracy , and in the practical application which has been verified . 2, in order to further improve the accuracy of the initial alignment of SINS large misalignment angle error conditions based on UKF filtering SINS initial alignment error model , the model is a nonlinear model , and applies to a wide range of system model noise and system measurement noise are complex additive noise , based on UKF ( Unscented Kalman filter ) filtering method . Considered to reduce the the filter computational needs and measurement equation can be simplified to the case of linear equations , and further simplified UKF filtering method . SINS initial alignment simulation test results show that the misalignment angle conditions SINS error model and the simplified UKF filtering method can effectively and quickly aligned system , can improve the alignment accuracy . 3 , the use of Kalman filtering techniques , the establishment of the state equation and measurement equation of SINS and GPS Navigation , and information fusion . On this basis , the application of the results of the study , designed and implemented the the SINS software system prototype .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radio navigation > Navigation systems of the various institutional > Complex navigation systems
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