Random drift real-time filtering method for fiber-optic gyroscope

Abstract

The invention discloses a random drift real-time filtering method for a fiber-optic gyroscope. Compared with the prior art, the method comprises the following steps: in a marine strap-down navigation attitude system, de-noising an acquired fiber-optic gyroscope signal in real time; decomposing data in a sliding data window according to the appointed number of layers through a second generation wavelet lifting algorithm to obtain wavelet coefficients of each layer and scale coefficients of the last layer; establishing corresponding threshold rules for the decomposed wavelet coefficients of each layer, and performing threshold quantization; combining the processed wavelet coefficients and the scale coefficients of the last layer, and progressively reconstructing the scale coefficients of each layer to obtain a de-noised signal. By virtue of the random drift real-time filtering method for the fiber-optic gyroscope, the real-time de-noising accuracy and the reaction speed of the fiber-optic gyroscope signal are effectively improved, so that attitude information errors are further suppressed. In an application process, parameters such as the width of the data window and the number of wavelet decomposing layers are easily set and can be set according to an experience value obtained by a simulation experiment.

Description

technical field [0001] The invention relates to a signal denoising method, in particular to a fiber optic gyroscope random drift real-time filtering method applied in a strapdown attitude system. Background technique [0002] The fiber optic gyroscope is a new type of all-solid-state gyroscope developed on the basis of the Sagnac effect. As one of the main inertial sensitive components, it is favored because of its potential best performance and cost ratio. It has become a new generation of low-to-medium Ideal inertial devices in precision strapdown inertial navigation and guidance systems. However, due to imperfect principles, processing and assembly processes, the gyro drift has become the main source of system errors, seriously affecting the initial alignment accuracy and navigation accuracy of the inertial navigation system. [0003] The drift of the fiber optic gyroscope includes two components: one is the regular and systematic drift with deterministic properties; the...

AI Technical Summary

Problems solved by technology

However, in actual situations, since the output of the fiber optic gyroscope is affected by a large amount of noise caused by detector noise, optical path noise, circuit noise and environmental changes, and these noises are time-varying, it is difficult to obtain accurate error statistics. Accurate Drift Model

Therefore, the ideal suppression effect cannot be obtained by using the first method

In addition, due to the unclear frequency domain characteristics of random drift, it increases the difficulty of digital filter design, and the second method also has its inherent defects

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