多MEMS陀螺数据融合方法性能比较

MEMS陀螺的体积小、成本低,便于集成,但其低精度极大的限制了MEMS陀螺在实际中的应用。利用多传感器融合技术进行误差补偿可提高MEMS陀螺的测量精度,人们提出了多种数据融合方法用于改进MEMS陀螺的测量精度。对多尺度融合方法、卡尔曼滤波融合和小波阈值融合方法进行比较分析。理论分析与实验结果表明,多尺度融合算法相比卡尔曼滤波融合和小波阈值融合方法在标准差、信噪比、功率谱及Allan方差等方面性能获得了较好的效果,其适用范围更宽。

Performance comparison of data fusion methods for multi MEMS gyroscopes

MEMS gyroscope has the advantages of small volume,low cost and easy integration,but its low accuracy greatly limits its application in practice.The measurement accuracy of MEMS gyroscope can be improved by using multi-sensor fusion technology for error compensation,so people have proposed many kinds of data fusion methods for improving the measurement accuracy of the MEMS gyroscope.In this paper,the multi-scale fusion method,the Kalman filter fusion and the wavelet threshold fusion method,are compared and analyzed.Theory analysis and experiments results show that,comparing with the Kalman filter fusion and the wavelet threshold fusion method,the multi-scale fusion algorithm has better performance on standard deviation,signal to noise ratio,power spectrum,and the Allan variance and so on,and it has a wider scope of the application.