Comparison of adaptive Kalman filter and zero-phase filter in processing gravity signal

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.