贝叶斯估计在静态倾角计算中的应用

Application of Bayesian estimation in static inclination calculation

目的:在采用三轴加速度计的倾角测量系统输出值解算中存在灵敏度非线性的情况下,为提高测量精度。方法:通过采集加速度传感器三个轴的测量值,应用三种不同的倾角计算方法对静态倾角进行计算;然后利用贝叶斯估计算法对计算结果进行数据融合计算。结果:融合计算结果的平均误差相比单一解算算法减小了77%以上,且误差分布更均匀。结论:采用贝叶斯估计融合以后的计算结果克服了单一算法固有的灵敏度非线性问题并且进一步降低了测量噪声,有效提高了静态倾角测量系统的测量精度。

Aims:To improve the measurement accuracy of the inclination measurement system with triaxial accelerometer nonlinear sensitivity.Methods:Firstly,the measured values of the three axes of the acceleration sensor were collected.Then,the static inclination angle was calculated by three different calculation methods.Finally,the Bayesian estimation algorithm was used for data fusion calculation.Results:The average error of the fusion results was reduced by more than 77%compared with the single algorithm,and the error distribution was more uniform.Conclusions:The results of Bayesian estimation fusion overcome the inherent sensitivity nonlinearity of the single algorithm and further reduce the measurement noise,which improves the measurement accuracy of the static inclination measurement system.