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Intelligent Information Processing for Inertial-Based Navigation Systems

  • Book
  • © 2021

Overview

  • Presents the adaptive de-noising algorithms to eliminate the noise of inertial sensors, based on the multi-scale analysis methods, such as wavelet analysis
  • Develops improved neural networks to establish and compensate the temperature drift model of gyroscope
  • Demonstrates discontinuous observation problem and proposes a self-learning Cubature Kalman filter based on deep learning for solving the problem
  • Discusses brain-like navigation scheme based on the navigation model of brain cells and the key technology such as position cell node matching method

Part of the book series: Navigation: Science and Technology (NASTECH, volume 8)

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Table of contents (7 chapters)

Keywords

About this book

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.

Authors and Affiliations

  • North University of China, Taiyuan, China

    Chong Shen

About the author

Dr. Chong Shen received his B.E. degrees in Measurement & Control Technology and Instrumentation from Yanshan University, Qinhuangdao, China, in 2008, and the M.E. and Ph.D. degree in Instrumentation Science and Technology from The Southeast University, Nanjing, in 2010 and 2014, respectively. Since June 2014, Dr. Shen has been in the School of Instruments and Electronics, North University of China, as  Associate Professor. 

Dr. Chong Shen focuses on the research of navigation systems based on inertial sensors. His recent research interests include inertial sensors error processing, information fusion algorithm for integrated navigation system, vision navigation system, and brain-like navigation system. His researches are funded by the National Natural Science Foundation, 863 Program, National Key Research and Development Projects. Since 2014, Dr. Shen has published more than 40 peer-reviewed technical papers in international journals such as IEEE TIE, MSSP, etc., which include more than 6 ESI high-cited papers. He is a member of IEEE and served as a reviewer of several international journals and a section chair of 2019 I2MTC international conference. He was a recipient of Excellent Young Academic Scholar—Award of Shanxi Province in 2018, and Outstanding Young Academic Scholar—Award of North University of China in 2019.




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