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以浮球式惯性平台上的光纤陀螺为研究对象,针对其输出原始数据噪声较大的问题,分别利用LMS自适应滤波算法、改进的小波实时降噪对光纤陀螺原始数据进行实时滤波处理。利用Matlab进行了陀螺数据模拟实时降噪实验,并对两种方法的降噪效果进行比较,结果表明两种方法对原始数据降噪都有明显效果,改进的小波实时降噪效果要优于LMS自适应算法。
Taking the FOG on the floating inertia platform as the research object, the original data of the FOG was filtered by LMS adaptive filtering algorithm and improved real-time wavelet denoising. Real-time noise reduction experiments using gyroscope data were simulated by Matlab, and the noise reduction effects of the two methods were compared. The results show that the two methods have significant effect on the noise reduction of the original data, and the improved wavelet real-time noise reduction effect is better than LMS Adaptive Algorithm.