A New Improved Adaptive Algorithm in Gravity Anomaly Processing

Abstract:

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.

• Periodical: Advanced Materials Research (Volumes 466-467)
• Pages: 556-560
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.466-467.556
• Online since: February 2012
• Authors: Cheng Luo, Hong Sheng Li, Li Ye Zhao
• Keywords: Adaptive Algorithm, Sage-Husa, Weighted Coefficients

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