分形滤波在高精度海洋重力仪数据处理中的应用研究

Application of Fractal Filtering in Gravitational Signal Processing

为有效地消除各种外界干扰噪声对高精度海洋重力仪测量值的影响,提高重力异常测量值的精度,在分析基于分形理论的滤波算法基础上,首次将其应用到高精度海洋重力仪系统数据处理中,并与自适应卡尔曼滤波进行对比分析,以实际信号数据与处理后信号数据的均方差作为衡量两种数据处理方法好坏的依据。理论分析和仿真实验表明:分形滤波方法和自适应卡尔曼滤波都能在一定程度上消除干扰噪声对重力异常信号的影响,但在相同背景条件下,分形滤波的性能优于自适应卡尔曼滤波。

The theory of fractal filtering is analyzed and applied to process the data measured by gravimeter in order to effectively alleviate the effect of different noise in high precise gravitational system. The average bias square between the true data and the processed data is used as the index for evaluating the performance of the data processing methods. Theoretical analysis and emulation experiments indicate that both fractal filtering and adaptive Kalman filtering are effective in alleviating the effects of different noise, but the performance of fractal filtering is better than that of adaptive Kalman filtering.