Bias and scale factor drift modeling methods for accelerometers
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摘要: 通过归纳工程上常用数据建模方法及其应用特点,且结合贮存条件下加速度计零偏和标度因数试验测量数据变化规律,综合给出了建立零偏时间序列模型和标度因数回归模型的详细步骤,并据此建立了贮存条件下加速度计零偏和标度因数的变化模型,所建模型预测的数据与真实数据相比误差很小,充分验证了模型的有效性.所建模型真实地反映了零偏随机性变化规律和标度因数趋势性变化规律的特点,可以为加速度计零偏和标度因数随时间变化的补偿模型提供参考,为加速度计参数长期变化稳定性水平评价提供手段.Abstract: Engineering data modeling methods and their application features were summarized, Combine with the accelerometer bias and scale factor drifting law of experimental measurements in storage conditions, bias time series analysis method and scale factor regression methodology were established respectively, and the detailed steps were also given. The bias and scale factor data of a certain accelerometer was given at last, and the drift values have been predicted via the presented method. The relative error between the prediction values and the measured data was small enough compared with the given acceptance level 10%, which shows the efficiency of the presented methods. The drift models reflect the bias great randomness drift feature and scale factor variation tendency description in true situation, and the accelerometer bias and scale factor drift models can not only be used in parameter exploration and drift compensation, but also provide long term stability assessment technique for the accelerometer bias and scale factor.
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Key words:
- accelerometer /
- regression analysis /
- time series analysis /
- bias /
- scaling factor
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