作品简介

本书系统而全面地阐述了仿生偏振光罗盘智能信息处理技术,总结了多年来在仿生偏振光罗盘信息处理方面的技术积累,并在书中进行详细阐述。主要包括:仿生偏振光罗盘噪声处理方法如偏振角图像和航向角数据噪声分析与处理、仿生偏振光罗盘定向误差建模补偿、基于仿生偏振光罗盘的无缝组合定向方法等,还详细介绍了基于大气偏振模式的航向角测量方法等相关内容。本书所有智能信息处理技术均配有试验验证,可作为导航制导与控制、仪器仪表、测绘工程及相关专业的本科生、研究生的参考书,也可供从事导航相关专业的科研和工程人员参考阅读。

赵东花,博士毕业于中北大学仪器科学与技术学科,研究方向为仿生传感与智能导航。现工作于中北大学"省部共建动态测试技术”国家重点实验室,讲师,日本大阪大学电气、电子和信息工程司访问学者。主持省部级课题2项,参与国家面上项目、装备重大基础研究课题、军委科技委173基金、军委科技委基础加强子课题等国家/省部级项目5项。以第一作者/唯一通信作者发表高水平SCI论文7篇,以第一发明人授权国家发明专利3项,独立编写国家级规划教材《传感器原理与应用》(第四版)一章。

作品目录

  • Introduction
  • PREFACE
  • Chapter 1 Introduction
  • 1.1 Development Background and Research Significance
  • 1.2 Bioinspired polarization orientation method
  • 1.3 Orientation error processing method for bioinspired polarization compass
  • 1.4 Combined orientation system and method for bioinspired polarizaition compass/inertial navigation
  • Chapter 2 Orientation Method and System for Atmospheric Polarization Pattern
  • 2.1 Orientation method for atmospheric polarization pattern
  • 2.1.1 Analysis and automatic identification of neutral point characteristics of atmospheric polarization pattern
  • 2.1.2 Orientation algorithm based on solar meridian for imaging bioinspired polarization compass
  • 2.2 Design and integration for bioinspired polarization compass based on FPGA
  • 2.3 Verification of Bioinspired Polarization compass orientation test
  • 2.3.1 Static orientation test
  • 2.3.2 Turntable dynamic orientation test
  • 2.3.3 UAV airborne dynamic orientation test
  • 2.4 Chapter Summary
  • Chapter 3 Processing technology for Bioinspired polarization compass noise
  • 3.1 Noise analysis for bioinspired polarization compass
  • 3.1.1 Analysis of the generation mechanism and characteristics for polarization angle image noise
  • 3.1.2 Analysis of the generation mechanism and characteristics for heading angle data noise
  • 3.2 Image denoising technology based on multi-scale transformation for bioinspired Polarization compass
  • 3.2.1 Denoising technology for polarization angle image based on multi-scale transformation
  • 3.2.2 MS-PCA Image Denoising Technology based on BEMD for Bioinspired Polarization Compass
  • 3.2.3 Verification of MS-PCA polarization angle image denoising method based on BEMD
  • 3.3 Heading data denoising technology based on multi-scale transformation for bioinspired polarization compass
  • 3.3.1 Heading data denoising technology based on multi-scale transformation
  • 3.3.2 MS-TFPF heading data denoising technology based on EEMD for bioinspired polarization compass
  • 3.4 Verification of heading data denoising based on multi-scale transformation for bioinspired polarization compass
  • 3.5 Chapter Summary
  • Chapter 4 Orientation error modeling and compensation technology for Bioinspired polarization compass
  • 4.1 Polarization orientation error analysis and model
  • 4.1.1 Analysis of polarization orientation error
  • 4.1.2 Model Construction for polarization orientation error
  • 4.2 Typical neural network models
  • 4.2.1 Recurrent Neural Networks (RNNs)
  • 4.2.2 Long Short-Term Memory Neural Networks (LSTMs)
  • 4.2.3 Gated Recurrent Unit Neural Networks (GRUs)
  • 4.3 Modeling and compensation of orientation error based on GRU deep learning neural network for bioinspired polarization compass
  • 4.4 Experimental verification of orientation error model based on GRU deep learning neural network for bioinspired polarization compass
  • 4.5 Chapter summary
  • Chapter 5 Seamless combined orientation method and system for bioinspired polarization compass/inertial navigation
  • 5.1 Seamless combined orientation system for bioinspired polarization compass/inertial navigation
  • 5.2 Seamless combination orientation model construction for bioinspired polarization compass/inertial navigation
  • 5.3 Seamless combined orientation method based on self-learning multi-frequency residual correction for bioinspired polarization compass/inertial navigation
  • 5.4 Experimental verification of the seamless combined orientation method for bioinspired polarization compass/inertial navigation
  • 5.5 Chapter summary
  • Chapter 6 Summary and prospect
  • 6.1 Summary of intelligent information processing technology for bioinspired polarization compass
  • 6.2 Research outlook
  • References
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