为解决光纤陀螺(FOG)信号滤波过程中噪声抑制与信号跟踪的矛盾,提出了一种自适应滑动平均离散小波变换——双模式卡尔曼滤波(AMA-DWT-DMKF)算法,利用AMA算法将FOG输出信号划分为信号过渡区域和稳定区域,并融合DWT算法和基于不同过程噪声方差Q/测量噪声方差R比条件下Kalman滤波算法的优势特性,对AMA算法判定结果进行针对性滤波。采用AMA-DWT-DMKF算法对FOG静态信号、扰动信号以及变化的速率信号进行滤波,实验结果表明,所提算法在保证较高噪声抑制能力的同时,具有较好的信号跟踪能力。
In order to solve the contradiction between noise suppression and signal tracking in filtering for fiber optic gyroscope (FOG), a method as AMA-DWT-DMKF is proposed. Using the AMA algorithm, FOG output signal is divided into a signal transition region and a stability region, and combining the advantages of two algorithms such as DWT and Kalman with different Q/R values, in the end giving a targeted filtering for the results of the AMA algorithm. The proposed method is used for denoising the static signal, disturbance signal and the change rate signal. Experimental results show that the proposed algorithm not only has higher denoising capability, but also has a better signal tracking capability.