基于复合卡尔曼的低成本手机陀螺仪降噪研究

Research on noise reduction of low-cost mobile phone gyro based on composite Kalman

在利用智能手机中的低成本MEMS传感器进行定位时,由于陀螺仪和加速度计输出的原始数据存在较大误差,难以获得较为准确的姿态角信息。其中利用陀螺仪数据进行积分运算后造成的漂移误差尤为严重。针对这个问题,将陀螺仪和加速度计的数据进行信息融合,使用复合卡尔曼滤波法来降低陀螺仪积分漂移误差。静态和摇摆实验表明基于复合卡尔曼滤波的降噪方法可有效提高姿态角测量精度。

When using low?cost MEMS sensors in smart phones for positioning,it is difficult to obtain accurate atti?tude angle information because of the large errors in the output data of gyroscopes and accelerometers.The drift er?ror caused by integral operation of gyroscope data is particularly serious.In order to solve this problem,the data of gyroscope and accelerometer are fused,and the integrated drift error of gyroscope is reduced by using compound Kalman filter.Static and swing experiments show that the noise reduction method based on Kalman filtering can ef?fectively improve the measurement accuracy of attitude angle.