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This book systematically elaborates on the intelligent information processing technology for a bioinspired polarization compass and inertial integrated navigation system. It consists of three parts. Firstly, the research background and significance of intelligent information processing technology for a bioinspired polarization compass are introduced. It analyzes the research status, development trends, and comparisons with foreign countries in the field of orientation methods based on atmospheric polarization patterns. The processing methods of the orientation error for a bioinspired polarization compass and integrated system information processing are also covered. Subsequently, the noise components of a bioinspired polarization compass and the impact of noise on its directional accuracy are discussed. It also introduces the denoising and orientation error compensation technique based on intelligent algorithms such as multi-scale principal component analysis and multi-scale adaptive time-frequency peak filtering. The third part focuses on the application of cubature Kalman filter and their improvement methods in seamless combination orientation systems based on a bioinspired polarization compass. A seamless combination orientation model under discontinuous observation conditions is proposed and a discontinuous observation algorithm based on neural networks is designed.
This book systematically elaborates on the intelligent information processing technology for a bioinspired polarization compass and inertial integrated navigation system. It consists of three parts. Firstly, the research background and significance of intelligent information processing technology for a bioinspired polarization compass are introduced. It analyzes the research status, development trends, and comparisons with foreign countries in the field of orientation methods based on atmospheric polarization patterns. The processing methods of the orientation error for a bioinspired polarization compass and integrated system information processing are also covered. Subsequently, the noise components of a bioinspired polarization compass and the impact of noise on its directional accuracy are discussed. It also introduces the denoising and orientation error compensation technique based on intelligent algorithms such as multi-scale principal component analysis and multi-scale adaptive time-frequency peak filtering. The third part focuses on the application of cubature Kalman filter and their improvement methods in seamless combination orientation systems based on a bioinspired polarization compass. A seamless combination orientation model under discontinuous observation conditions is proposed and a discontinuous observation algorithm based on neural networks is designed.
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