摘要
针对微机电系统(MEMS)陀螺测量精度低、随机噪声复杂的问题,根据MEMS陀螺的实测数据,分析其噪声特性,研究MEMS陀螺的随机噪声模型。应用时间序列分析方法,采用时间序列分析(AR)模型对MEMS陀螺测量数据噪声进行建模,该模型反映陀螺的噪声特性,基于该随机噪声模型,采用Kalman滤波技术有效降低了随机噪声对MEMS陀螺测量精度的影响。通过对MEMS陀螺实测数据的仿真试验结果表明:提出的建模与滤波方法能够有效地抑制其随机噪声误差,提高实际应用中的测量精度。
For the problem of low accuracy and complex random noise of MEMS gyroscope, according to the measured data of MEMS gyroscope, the noise characteristics are analyzed, and the MEMS gyro＇ s drift model is designed. Time series analysis method is used. MEMS gyro noise measurement data are analyzed using AR model. Kalman filtering is adopted to decrease the effect of random noise of MEMS gyroscope, based on the AR model. The measured data of MEMS gyroscope simulation test results show that the proposed modeling and filtering method can ef- fectively restrain the noise error and improve the measuring precision in practical application.
出处
《微型机与应用》
2016年第24期81-83,共3页
Microcomputer & Its Applications
基金
国家自然科学基金(61305050)
