Gravity data fusion using wavelet transform and window weighting: a case study in the Ross Sea of Antarctica

Satellite gravity anomaly data are characterized with wide coverage and high overall normalized quality, and these data can be used in large-scale regional structural research. However, detailed information on local areas is often missing after smoothing. High-resolution ship-borne gravity anomaly data can better identify fault zones and block boundaries at key locations, compensating for low-resolution satellite gravity data. In this study, comprehensive gravity data derived from multiple techniques are used based on wavelet transforms, the fusion rules for high- and low-frequency wavelet coefficients are established, and the complementary use and effective fusion of gravity data derived from multiple techniques are realized. By collecting a large amount of ship-borne data in the Ross Sea of Antarctica, 1434 valid survey lines with a total length of 98,204 km are obtained in the study area. After adjustment, the root mean square of the crossover errors is ± 1.92 × 10^–5 m/s². Here, different wavelet functions and decomposition levels are used, the concept of window weighting is introduced, and the useful information of the two data types is further fused. Thus, higher-resolution data are obtained with less errors. When fusing all line data, the minimum RMS difference between the optimal fusion result and the ship measurement data is 1.64 × 10^–5 m/s², which increases the accuracy by 1.66 × 10^–5 m/s². When we adopt 80% data fusion and the remaining 20% data validation, although a considerable portion of the remaining side lines are still distributed in areas that the original side lines cannot cover, using this method can still effectively improve the accuracy of the fused data. This method can be applied to most gravity data.