摘要
随机漂移是影响微机电系统(MEMS)陀螺仪精度的主要因素。为了实时估计并补偿随机漂移,对启发式漂移消减算法(HDR)进行改进,提出自适应漂移消减算法。利用Allan方差分析方法确定陀螺仪的零偏稳定时间,通过检测陀螺仪数据的平稳性来区分随机漂移和真实角速率。以Pioneer3—AT机器人为平台进行试验,与基本HDR算法相比,新算法可以弥补载体有恒定角速率时基本HDR算法不可用的缺点,与普通算法相比,新算法可以提高航向精度2倍以上。
Random drift is the main factor that influences the precision of micro-electro-mechanical system （MEMS） gyroscope. In order to real-time estimate and compensate random drift and improve on heuristic drift reduction algorithm self-adaptive drift reduction algorithm was proposed. Allan-variance analysis method was adopted to determine the null bias stability time of gyro. Random drift and true angular rate were distinguished by checking the stationary character of gyro. Test had been done with the platform of gyro-equipped indoor mobile robot Pioneer3-AT. When the body has a constant true angular rate, the new algorithm is still useful while the basic heuristic drift reduction algorithm is not use. To compare with common algorithm, the new method can increase the precision by 2 times.
出处
《传感器与微系统》
CSCD
北大核心
2010年第3期109-111,114,共4页
Transducer and Microsystem Technologies
