ARMA time-series north-searching method based on optical fiber gyroscope

Abstract

The invention discloses a north finding method of ARMA time sequence based on an optical fiber gyro. Before the process of data processing, the invention analyzes the output sequence of a plurality of optical fiber gyros with different models in a north finding system to determine that for the series of numbers in the original series of numbers, which goes through random stationarity processing, the fitting of ARMA (2, 1) model can be implemented with the best effect; therefore, the invention proposes the establishment of an output model of a north finding testing fiber gyro by using ARMA and offers a whole proposal of parameter solving and model building. First, the proposal reduces the error of the north finding model fitting, thus leading the fitted model to be closer to the property of original series of numbers. The model has higher accuracy and certain university in the north finding technology and provides a foundation for the application of subsequent filter methods such as kalman filter which needs relatively accurate north finding models and the like. In addition, in regard to the solving of model parameters, fixed solving steps and the establishment method of a model of the original series of numbers are proposed, thus improving the speed and efficiency of data processing in the north finding testing.

Description

technical field [0001] The invention relates to a north-seeking method, in particular to a north-seeking method based on an ARMA time series of an optical fiber gyroscope. Background technique [0002] Based on the inertial sensing effect, the fiber optic gyroscope has obvious advantages over other types of gyroscopes in terms of no moving parts, firmness and stability, impact resistance and acceleration resistance. As a sensitive element, it has broad application prospects in north-seeking technology, positioning and orientation. In the analysis of the time series output by looking for the north, the time series analysis method is undoubtedly a relatively good and theoretically complete statistical forecasting analysis method, and it is also able to analyze and predict the time series, as well as identify, estimate and analyze the ARMA model. A systematic approach to diagnosis. Among them, the establishment of the ARMA model has a set of complete, regular and structured mo...

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Problems solved by technology

At present, in the establishment of the model of the fiber optic gyroscope output signal for the north-seeking test, when using time series analysis, fixed models are mostly used, such as ARMA(2,1), AR(2) or MA model, while ignoring the Statistical analysis is performed on the model of the north-seeking test fiber optic gyro output sequence; and in the process of data analysis, the non-stationary and non-random characteristics of the north-seeking output sequence are ignored, and the sequence is not independent, stable, normal, zero-mean, etc. However, the ARMA model is directly used for analysis, which basically does not conform to the characteristic that the time series is suitable for a stationary random sequence, so the fitted model has a relatively large error

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