为了有效消除海洋重力仪测量信号的噪声,提高重力数据的获取精度,根据随机过程理论,借助基于二阶高斯一马尔可夫异常位模型的重力异常协方差函数,得到海洋重力测量中重力异常信号的状态方程.对sage-husa滤波算法和零相移算法进行了理论分析,为了抑制零相移滤波器的首尾数据畸变,求解了滤波器的初始状态.根据实测重力数据,进行了去噪仿真试验.理论分析和仿真结果表明,sage-husa与零相移滤波算法均能较好地抑制采样重力数据中的噪声干扰,但零相移滤波算法的性能优于sage-husa滤波器.%In order to effectively eliminate the noise of the measurement gravity and improve the accuracy of the gravity signal, the state equation of gravity anomaly signal is derived in marine gravimeter by using the theory of random process and gravity anomaly covariance function based on second-order Gaussian Markov gravity anomaly potential model. The algorithms of sage-husa and zero-phase are theoretically analyzed for contrast. The initial state of zero-phase filter is calculated to inhibit the distortion of the signal. Based on real gravity data, the de-noising simulation experiment is made. The results of theoretical analysis and simulation experiments indicate that both the zero-phase filter and the sage-husa filter can effectively eliminate the noise of real gravity data, but the zero-phase filter could achieves better performance than the sage-husa filter.
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