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机载经度、纬度、高度数据的精度,对保证飞机定位的精确性和飞行安全性有着重要意义。结合小波分解和经验模态分解(EMD)2种方法的优点,在小波分解的基础上,提出1种基于EMD的小波分解降噪方法。利用EMD对机载位置数据进行分解,并对高频分量用小波分解方法进行降噪处理,降噪后高频分量再结合低频分量进行重构得到降噪后的数据。以西安到长春某航班巡航阶段的机载高度数据序列为例,进行了仿真验证。结果表明,改进小波分解降噪方法与传统的小波分解降噪方法相比,信噪比提高了0.649,均方根误差减小了0.696 9,消噪效果更加明显。改进的小波分解方法在处理机载位置数据方面有着较明显的优点,可获得更精确的飞机三维数据。
The accuracy of airborne longitude, latitude and altitude data is of great significance to ensure the accuracy of aircraft positioning and flight safety. Combining the advantages of two methods of wavelet decomposition and empirical mode decomposition (EMD), a wavelet denoising method based on EMD is proposed based on wavelet decomposition. The EMD is used to decompose the airborne position data, and the high frequency components are denoised by the wavelet decomposition method. After noise reduction, the high frequency components are reconstructed with the low frequency components to obtain the denoised data. Taking the airborne altitude data sequence during the cruise phase of a flight from Xi’an to Changchun as an example, the simulation is carried out. The results show that compared with the traditional wavelet decomposition denoising method, the improved wavelet decomposition denoising method improves the signal-to-noise ratio by 0.649, the root mean square error decreases by 0.696 9, and the denoising effect is more obvious. The improved wavelet decomposition method has obvious advantages in dealing with the on-board position data and can obtain more accurate three-dimensional data of the aircraft.