Improved Extended Kalman Filter Estimation using Threshold Signal Detection with a MEMS Electrostatic Microscanner.
Improved Extended Kalman Filter Estimation using Threshold Signal Detection with a MEMS Electrostatic Microscanner.
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DOI：
10.1109/tie.2019.2901663
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发表时间：
2020-03
期刊：
影响因子：
--
通讯作者：
Oldham KR
中科院分区：
文献类型：
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作者：
Chen Y;Li H;Qiu Z;Wang TD;Oldham KR
提出了一种阈值信号检测器来提高扩展卡尔曼滤波器 (EKF) 的状态估计精度，并通过 MEMS 静电微扫描仪进行了实验验证。高斯一阶导数 (DOG) 滤波器用于检测和定位由于跨越电容电极最大重叠所确定的阈值角度而引起的电压信号的快速变化。事件触发测量用于 EKF 的更新步骤，以提供间歇性但比电容式传感器连续输出更准确的角度测量。在静电微扫描仪上的实验表明，结合阈值信号检测器后，EKF的平均位置估计精度提高了15.1%，其中在低信噪比（SNR）条件下提高幅度最大（30.3%）。进行参数研究以检查采样频率和电容分布以及可能影响检测误差和 EKF 精度的其他因素。
A threshold signal detector is proposed to improve the state estimation accuracy of an extended Kalman filter (EKF) and is validated experimentally with a MEMS electrostatic micro-scanner. A first order derivative of Gaussian (DOG) filter is used to detect and locate rapid changes in voltage signal caused by crossing of a threshold angle determined by maximum overlap of capacitive electrodes. The event-triggered measurement is used in the update step of the EKF to provide intermittent but more accurate angle measurements than those of the capacitive sensor’s continuous output. Experiments on the electrostatic micro-scanner show that with the threshold signal detector incorporated, the average position estimation accuracy of the EKF is improved by 15.1%, with largest improvement (30.3%) seen in low signal-to-noise ratio (SNR) conditions. A parametric study is conducted to examine sampling frequency and capacitance profile, among other factors that may affect detection error and EKF accuracy.