Error processing method for output signal of optic fiber gyroscope component

Abstract

The invention discloses an error processing method of the output signal of an optical-fiber scopperil component and belongs to the error processing methods of the output signal of an optical-fiber scopperil component in an inertial navigation system. The concrete steps of the processing method are that: an output signal model of the optical-fiber scopperil component and an error model thereof are built; the marking and the compensation of the fixed error of the optical-fiber scopperil component are implemented; the self-adaptive filtering of the random error of the optical-fiber scopperil component is implemented. The processing method effectively reduces the zero-offset drift of the optical-fiber scopperil component which is caused by temperature changes, has high marking precision of the fixed error, high marking efficiency and good adaptability; furthermore, the processing method effectively reduces the random error of optical-fiber scopperil, has small amount of computation, and is suitable for real industrial applications.

Description

1. Technical field [0001] The invention relates to a signal processing method of an inertial sensor in an inertial navigation system, in particular to an error processing method for an output signal of an optical fiber gyroscope assembly. 2. Background technology [0002] The inertial navigation system is based on Newton's relative inertial space mechanics law, using inertial sensors (including gyroscopes and accelerometers) to sense the angular velocity and acceleration of the vehicle, and obtain the navigation parameters such as the attitude, speed and position of the vehicle through integral operations. As the core component of the inertial navigation system, the inertial sensor is composed of three gyroscopes (gyroscope components) and three accelerometers (accelerometer components) whose sensitive axes are orthogonal to each other. The output error is an important factor affecting the accuracy of the inertial navigation system. [0003] The fiber optic gyroscope is an a...

AI Technical Summary

Problems solved by technology

The conventional fixed error calibration method often does not take into account the sensitivity of the FOG zero bias to temperature, resulting in unsatisfactory calibration of error parameters; the method of using Kalman filtering for random error processing is not practical because it is difficult to obtain an accurate error model; When neural network technology is applied to random error processing, it will bring real-time problems; while conventional LMS adaptive filtering methods are difficult to obtain good comprehensive performance in terms of filtering accuracy, real-time performance, and dynamic input range.

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