Intelligent Information Processing for Inertial-Based Navigation Systems (Navigation: Science and Technology, 8)

✍ Scribed by Chong Shen

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 131
• Category: Library

✦ Synopsis

This book introduces typical inertial devices and inertial-based integrated navigation systems, gyro noise suppression, gyro temperature drift error modeling compensation, inertial-based integrated navigation systems under discontinuous observation conditions, and inertial-based brain integrated navigation systems. Integrated navigation is the result of the development of modern navigation theory and technology. The inertial navigation system has the advantages of strong autonomy, high short-term accuracy, all-day time, all weather, and so on. And it has been applied in most integrated navigation systems. Among them, the information processing of inertial-based integrated navigation system is the core technology. Due to the effect of the device mechanism and working environment, there are errors in the output information of the inertial-based integrated navigation system, including gyroscope noise, temperature drift, and discontinuous observations, which will seriously reduce the accuracy and robustness of the system. And the book helps readers to solve these problems. The intelligent information processing technology involved is equipped with simulation verification, which can be used as a reference for undergraduate, graduate, and Ph.D. students, and also scientific researchers or engineers engaged in navigation-related specialties.

✦ Table of Contents

Preface
Contents
1 Introduction
2 Synopsis of Typical Inertial Sensors and System
2.1 Fiber Optic Gyro
2.2 MEMS Gyro
2.3 Inertial Navigation System
2.3.1 Strapdown Inertial Navigation System
2.3.2 Overview of Basic Principles of Inertial Navigation System
2.3.3 Basic Algorithm of Strapdown Inertial System
3 Noise Analysis and Processing Technology for Gyroscope
3.1 Components of Gyro Noise and Allan Analysis Method
3.1.1 Source and Characteristic Analysis of Gyro Noise
3.1.2 Allan Variance
3.2 Denoising Algorithm for Fog Signal
3.2.1 Enhance the Wavelet Transform
3.2.2 Forward Linear Prediction Algorithm
3.2.3 LWT-FLP Algorithm
3.2.4 Analysis of De-Noising Results of Fog Signal
3.3 The Method of Eliminating the Angular Vibration Error of Fog
3.3.1 Angular Vibration Experiment and Output Signal Analysis
3.3.2 Grey FLP Algorithm
3.3.3 G-FLP Algorithm
3.4 Summary
4 Temperature Drift Modeling and Compensation for Gyroscope
4.1 Temperature Drift and Modeling Method of Fog
4.2 Fiber Gyro Temperature Error Model Based on External Temperature Change Rate
4.3 Temperature Drift Modeling and Compensation Based on Genetic Algorithm and ELMAN Neural Network
4.3.1 Neural Network
4.3.2 Elman Neural Network
4.3.3 Genetic Algorithm
4.3.4 GA-Elman-Based Fiber Optic Gyro Temperature Drift Modeling and Compensation
4.4 Summary
5 Model and Algorithm for Discontinuous Observation Integrated Navigation System
5.1 Solutions and Typical Models of Discontinuous Observation Integrated Navigation System
5.2 Application of Kalman Filter and Neural Network in Integrated Navigation of Non-continuous Observation
5.2.1 Strong Tracking Kalman Filtering
5.2.2 Wavelet Neural Network
5.2.3 Experimental Results and Analysis
5.3 Application of Self-learning Cubature Kalman Filter in Combined Navigation
5.3.1 Square Root Cubature Kalman Filter
5.3.2 Long-Short Term Memory Neural Network
5.3.3 Self-learning Volume Kalman Filter
5.3.4 Experimental Results and Analysis
6 Brain-Like Navigation Technology Based on Inertial/Vision System
6.1 Overview of Bionic Navigation Background
6.2 Bionic Navigation Mechanism
6.2.1 Positional Cell
6.2.2 Head Direction Cell
6.2.3 Grid Cell
6.2.4 Velocity Cell
6.2.5 Brain Navigation System
6.3 High-Speed Effective Node Matching Algorithm
6.3.1 Scan Line Strength
6.3.2 GMS (Grid-Based Motion Statistics)
6.3.3 Scan Line Intensity/GMS
6.4 Algorithm Verification
7 Concluding Remarks
7.1 Summary of Inertial-Based Navigation Intelligent Information Processing Technology
7.2 Research Prospect
Bibliography