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A discrimination method for accelerometer static model parameter based on nonlinear iterative least squares estimation

机译:基于非线性迭代最小二乘估计的加速度计静态模型参数判别方法

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The accelerometer is the one of the core inertial measurement components in inertial navigation system. The velocity and position of transporting species are obtained by carrying on one and two integrals respectively to the accelerometers outputs. So, the precision of navigation system is obviously affected by the static error of accelerometer. In this paper, the static mathematics model of accelerometer is built firstly and the static parameters are estimated with gravitational field static tumbling test method next. Consider that the initial installation error angle of accelerometer exists and can not be neglected in gravitational field static tumbling test method, we get a nonlinear static mathematics model of accelerometer including the installation error angle. To this nonlinear model, a nonlinear iterative least squares estimation is used to estimate the static parameters of accelerometer with the measurement data coming from gravitational field tumbling test method. Finally, a simulation experiment show that the accelerometer static parameters with this discrimination method can achieves high precision.
机译:加速度计是惯性导航系统中的核心惯性测量组件之一。通过分别对加速度计输出进行一个和两个积分来获得运输物质的速度和位置。因此,导航系统的精度明显受到加速度计静态误差的影响。本文首先建立了加速度计的静态数学模型,然后利用重力场静态翻滚试验方法估算了静态参数。考虑到加速度计的初始安装误差角存在并且在重力场静态翻滚试验方法中不能忽略,我们得到了一个加速度计的非线性静态数学模型,其中包括安装误差角。对于该非线性模型,使用非线性迭代最小二乘估计来估计加速度计的静态参数,其中的测量数据来自重力场翻滚测试方法。最后,通过仿真实验表明,该判别方法可以使加速度计的静态参数达到较高的精度。

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