A LSTM Fiber Optic Gyroscope Temperature Compensation Modeling Method Based on Deep Embedded Clustering

Abstract

The invention discloses an LSTM fiber optic gyroscope temperature compensation modeling method based on deep embedded clustering, which includes: collecting temperature and fiber optic gyroscope zero bias data to construct a training data set, and training a denoising autoencoder layer by layer; Noisy autoencoder, constructing a deep autoencoder; based on a deep autoencoder, mapping the input x to obtain an embedded point z; calculating the soft allocation between the embedded point z and the cluster center, and constructing an auxiliary target allocation; using soft allocation and auxiliary target allocation The kl divergence is the objective function, iterates between calculating the auxiliary objective function and minimizing the kl divergence, updating the depth autoencoder parameters and cluster centers; segmenting according to the clustering results, using LSTM neural network on each segment The temperature compensation model of the fiber optic gyroscope is obtained through training. The invention can realize the temperature compensation of the gyroscope output zero bias error, obtain good fitting and prediction effects and high temperature environment adaptability, and improve the product precision of the optical fiber gyroscope.

Description

technical field [0001] The invention relates to the technical field of fiber optic gyroscopes, in particular to an LSTM fiber optic gyroscope temperature compensation modeling method based on deep embedding clustering. Background technique [0002] The influence of temperature is one of the main factors restricting the performance of the fiber optic gyroscope. When the working environment temperature changes, it will cause the zero position drift of the gyroscope output signal. It must be temperature compensated to improve the performance. At present, some machine learning algorithms have been applied to the establishment of gyro temperature compensation models, such as support vector machines, wavelet neural networks, RBF neural networks, etc. [0003] In "Piezoelectricity and Acousto-optic" "Optical Fiber Gyroscope System-Level Temperature Compensation Based on Wavelet Neural Network", a method for temperature compensation of fiber optic gyroscope based on wavelet neural n...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the defect of artificial segmentation fitting of the fiber optic gyroscope temperature compensation model existing in the current technology, the present invention provides a LSTM fiber optic gyroscope temperature compensation modeling method based on deep embedding clustering

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