基于ARMA的微惯性传感器随机误差建模方法

针对微惯性传感器随机误差建模效果不理想,影响微惯性组合导航系统性能的问题,提出了采用自回归滑动平均(ARMA)对微惯性传感器随机误差进行建模的方法。通过对随机误差模型应用于微惯性器件误差建模的深入分析,将Yule-Walker方程引入线性预测问题中,实现AR功率谱密度的估计,建立了基于随机过程有理功率谱密度的ARMA模型建立方法,并给出了ARMA建模准确性的LDA验证准则。通过微惯性传感器实测数据,对随机误差建模方法进行了有效性验证。该方法为微惯性器件的随机误差建模和分析提供了一种新的途径。

Stochastic error modeling method for micro inertial sensor based on ARMA

Aiming at problem that the characteristic of the micro inertial integrated navigation system is seriously influenced by effect of stochastic error modeling,a stochastic error modeling method using auto regressive moving average(ARMA) for micro inertial sensor is proposed.Through analysis on application of stochastic error model in micro inertial device error modeling,introducing Yule-Walker equation to linear prediction problems,estimation of AR power spectral density is achieved.ARMA models are set up based on rational power spectral density of stochastic process.Actual data validates the effectiveness of modeling methods.This method provides a new approach for modeling and analysis of stochastic errors.