根据QMEMS陀螺的特性,在对现有卡尔曼滤波方法分析的基础上,根据自适应滤波理论和UD分解理论,提出了一种改进型自适应滤波方法,该方法可去除QMEMS陀螺在采样过程中产生的异常值,并增强惯性导航系统的实时性和稳定性.通过对QMEMS陀螺实际输出数据的滤波仿真显示,该方法去噪效果明显好于卡尔曼滤波方法,利用该方法时QMEMS陀螺的采样数据进行处理,可以为惯性导航解算提供更为准确的数据,提高惯性导航系统的精度.%According to the characteristics of quartz micro-electro-mechanical systems (QMEMS) gyro, adaptive filtering and UD decomposition theories, an improved adaptive method based on Kalman filtering method is proposed. This method removes the error data during sampling and enhances the real-time performance and stability of inertial navigation system. The simulation results of QMEMS gyro output show that the improved adaptive filtering is much better than Kalman filtering on de-noise effect. The improved adaptive filter provides more accurate data for inertial navigation system, and the precision of inertial navigation is improved.
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