为了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，在分析了小波阈值及自适应小波阈值去噪算法的基础上，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做了对比，以处理后信号的信噪比作为衡量3种数据处理方法优劣的依据。理论分析和仿真实验表明，自适应小波阈值去噪方法、传统的小波阈值去噪方法和自适应卡尔曼滤波都能在一定程度上消除噪声信号对重力仪测量信号的影响，但在相同情况下，自适应小波阈值去噪方法具有明显的优越性。

The theory of wavelet thresholding denoising 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 signal to noise ration (SNR) is used as the index for evaluating the performance of the data processing methods. Theoretical analysis and emulation experiments indicate that wavelet thresholding denoising, adaptive wavelet thresholding denoising and adaptive Kalman filtering are all effective in alleviating the effects of different noise, but the performance of adaptive wavelet thresholding denoising is best.