摘要
通过中值滤波和均值滤波的有机结合,可以去除MEMS陀螺仪漂移中的"野点"信号。基于Haar小波基的小波变换,寻找到了一种易于实时在线实现的漂移特征提取方法。对残差信号进行二阶AR模型分析建模后,利用改进的自适应Kalm an滤波算法,对残差信号进行滤波,提高了被处理漂移信号的精度。实际测量数据的处理结果验证了该MEMS陀螺仪去漂移方法的有效性。
The outlier signal from the MEMS gyro drift could be got rid of effectively by uniting the mean filter and the median filter. Based on the wavelet transformation of the Haar basis, a method to extract the character of the gyro drift signal has been found ,the method is fit for the implementation in real-time on-line. After the residual signal is modeled by a 2-order AR, an improved adaptive Kalman filtering algorithm is used to filter the signal. The accuracy of drift signal is improved greatly. The processed result from the practical gyro measurement shows the method of the de-drift is effective.
出处
《传感器与微系统》
CSCD
北大核心
2006年第9期79-81,85,共4页
Transducer and Microsystem Technologies
基金
国家"863"计划资助项目(2002AA812038)