Combined with the system state equation and the measurement equation, a new method of cascade Kalman filter is proposed and applied to the correction of gravity anomaly distortion. In the signal processing procedure, according to the self-correlation sequences of the measurement gravity signal, the relation of the gain matrix K and the self-correlation sequences could be obtain, and the gravity signal at current time can be calculated by the gain matrix K. Emulations and experiments indicate that both the cascade Kalman filter method and the single inverse Kalman filter method are effective in alleviating the distortion of the gravity anomaly signal, but the performance of the cascade Kalman filter method is better than that of single inverse Kalman filter method.
In order to effectively eliminate the measurement and system noise and improve the accuracy of the gravity anomaly, based on the sage-husa filter, a modified adaptive Kalman filter is proposed. The sum of the weighted innovation sequence is used as the innovation at current time, and then system parameters Q and R can be estimated by the innovation. The adaptive algorithm is conducted theoretically and based on the real gravity data, the de-noising experiment has been emulated. The simulations indicate that both filters can effectively inhibit the noise of inertial/gravity system, but the proposed filter has a better performance than sage-husa adaptive filter.
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