CHEN Guangwu1，2, YU Yue1，2, LI Wenyuan1，2, LIU Hao1，2
（1. Automatic Control Research Institute, Lanzhou Jiaotong University, Lanzhou 730070， China；2. Gansu Provincial Key Laboratory of Traffic Information Engineering and Control, Lanzhou 730070， China）
Abstract： Aiming at the problems of low measurement accuracy, uncertainty and nonlinearity of random noise of the micro electro mechanical system (MEMS) gyroscope, a gyroscope noise estimation and filtering method is proposed, which combines expectation maximum (EM) with maximum a posterior (MAP) to form an adpative unscented Kalman filter (UKF), called EMMAP-UKF. According to the MAP estimation principle, a suboptimal unbiased MAP noise statistical estimation model is constructed. Then, EM algorithm is introduced to transform the noise estimation problem into the mathematical expectation maximization problem, which can dynamically adjust the variance of the observed noise. Finally, the estimation and filtering of gyroscope random drift error can be realized. The performance of the gyro noise filtering method is evaluated by Allan variance, and the effectiveness of the method is verified by hardware-in-the-loop simulation.
Key words： micro electro mechanical system (MEMS) gyroscope; expectation maximization (EM) algorithm; noise estimation; unscented Kalman filter (UKF)
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基于EMMAP的MEMS陀螺噪声估计与滤波方法研究
陈光武1，2， 于 月1，2， 李文元1，2， 刘 昊1，2
（1. 兰州交通大学 自动控制研究所， 甘肃 兰州 730070； 2. 甘肃省高原交通信息工程及控制重点实验室， 甘肃 兰州 730070）
摘 要: 针对MEMS陀螺仪测量精度低、 随机噪声具有不确定性和非线性的问题， 提出一种基于最大期望算法（Expectation maximum, EM）和极大后验估计（Maximum a posterion, MAP）的无迹卡尔曼滤波（Unscented Kalman filter, UKF）——EMMAP-UKF的陀螺噪声估计与滤波方法。 根据极大后验估计原理， 构造出一种次优无偏MAP噪声统计估计模型， 并在此基础上引入最大期望算法将噪声估计问题转换为数学期望极大化问题， 实现对观测噪声方差的动态调整， 最终实现陀螺仪随机漂移误差的估计与滤波处理。 最后通过Allan方差对陀螺噪声滤波方法的性能进行评估， 通过半实物仿真验证了本方法的有效性。
关键词: MEMS陀螺仪； 最大期望算法； 噪声估计； 无迹卡尔曼滤波
引用格式： CHEN Guangwu, YU Yue, LI Wenyuan, et al. Noise estimation and filtering method of MEMS gyroscope based on EMMAP. Journal of Measurement Science and Instrumentation, 2021, 12（2）： 170-176. DOI： 10.3969／j.issn.1674-8042.2021.02.006
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