Joint noise reduction method for signals of fiber-optic gyroscope inertial measurement unit

Abstract

The invention provides a fiber-optic gyroscope IMU (Inertial Measurement Unit) signal joint noise reduction method, which comprises the following steps of: firstly, carrying out intrinsic mode component IMF decomposition on a fiber-optic gyroscope IMU output signal by utilizing a fast self-adaptive noise complete set empirical mode decomposition method Fast-CEEMDAN, so that the calculation amount is greatly reduced, meanwhile, the problem of noise transfer from high frequency to low frequency is effectively solved, and the precision and efficiency of information structuring are improved; then, calculating the permutation entropy and the average permutation entropy of the IMF, and achieving the screening of the IMF with more noise; and finally, de-noising the IMF with more noise by using adaptive wavelet packet analysis and AWPA methods, ensuring no redundancy of signal decomposition, reducing local signal loss, and improving the signal-to-noise ratio of the signal to the maximum extent, thereby obtaining high-precision and strong-robustness measurement information.

Description

technical field [0001] The invention belongs to the field of noise reduction, and in particular relates to a signal joint noise reduction method of a fiber optic gyroscope inertial measurement unit. Background technique [0002] Limited by fiber optic surround manufacturing technology and integrated packaging technology, the current miniaturized fiber optic gyro IMU is extremely sensitive to electronic and mechanical noise, and the output signal contains large high-frequency random noise, which seriously affects the performance of the fiber optic gyro IMU. Measurement accuracy, so it is necessary to perform noise reduction on its output signal. [0003] At present, the fiber optic gyroscope IMU signal denoising processing methods mainly include Kalman filter method, wavelet analysis method, empirical mode decomposition (Empirical Mode Decomposition, EMD) method, etc. [0004] The Kalman filter denoising method is a recursive filter method, which can obtain the optimal estim...

AI Technical Summary

Problems solved by technology

However, this method needs to add adaptive white noise multiple times in the process of calculating each level of Intrinsic Mode Function (IMF), which makes the calculation more complicated and reduces the efficiency of the method.

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