小波多尺度分析在重力仪数据处理中的应用研究

Application of Wavelet Multiresolution in Gravitational Data Processing

为了有效地消除重力异常畸变对重力仪测量数据的影响,得到更高精度的重力异常测量值,在分析小波多尺度分析原理的基础上,首次将其应用到重力仪数据处理中,并与自适应卡尔曼滤波进行了对比分析,以实际数据与处理后数据偏差平方和的平均数作为衡量两种数据处理方法性能的指标。理论分析和仿真实验表明:小波多尺度分析和自适应卡尔曼滤波都能在一定程度上抑制重力异常畸变对重力仪测量数据的影响,但小波多尺度分析的性能优于自适应卡尔曼滤波。

The theory of wavelet multiresolution and adaptive Kalman filtering is analyzed and firstly applied to process the data measured by gravimeter in order to effectively alleviate the effect of gravitational abnormal deform 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 wavelet multiresolution and adaptive Kalman filtering are effective in alleviating the effects of gravitational abnormal deform, but the performance of wavelet multiresolution is better than that of adaptive Kalman filtering.