中文摘要：

为了有效抑制高精度重力测量信号中的各种强噪声以获得高精度重力信息,在分析形态小波滤波算法的基础上,结合FFT算法提出了一种快速形态小波滤波算法,并应用于高精度重力仪信号处理中.在滤波过程中,首先在常规小波分解算法各层间增加形态滤波器,以提高小波算法抑制脉冲干扰的能力.然后,将常规小波分解和重构算法进行重组,并参考FFT算法规则设计了一种快速形态小波分解重构算法,以提高小波分解和重构的计算效率.最后,通过仿真试验,将快速形态小波滤波算法与传统小波滤波算法进行性能对比.理论分析和仿真试验结果表明,快速形态小波算法的滤波效果优于传统小波滤波,其运算速度优于Mallat算法.

英文摘要：

Combined with the fast Fourier transformation（FFT） method,a fast morphological wavelet filter algorithm is proposed based on the morphological wavelet algorithm and applied to the precise gravimeter signal processing in order to suppress serious background noises and get high precise gravity information.The preliminary work is to add the morphological filter to each level of the classical wavelet decomposition to suppress the impulse noise.Then,the regular wavelet decomposition and reconstruction algorithms are reconstructed.With reference to the FFT method,the fast morphological wavelet decomposition and reconstruction algorithms are designed to increase the computational efficiency.Finally,the performances of the fast morphological wavelet filter and the classical wavelet filter are compared by simulation.Theoretical analysis and simulation results show that the denoising performance of the proposed method is better than that of the classical wavelet algorithm and the computation speed is superior to that of the classical Mallat algorithm.