A Shifted Double Wavelet Iteration Algorithm for Detecting the Gross Errors in Shipborne Gravity

Abstract

Detecting the discrete gross error and regional gross error in shipborne gravity is a key step for improving the measurement quality. The traditional wavelet threshold shrinkage (WTS) method misidentifies discrete gross errors and cannot detect regional gross errors. Here we propose a shifted double wavelet iteration (SDWI) method. This method decomposes the measurement sequence by shifted double wavelet to obtain wavelet coefficients, and then apply threshold processing to the obtained coefficients to accurately detect gross errors. After that, we reconstruct the identified gross errors, and perform iterative processing to the regional gross errors. Finally, the difference of the gravity before and after gross error detection is used for gross error positioning. In the simulation experiment, we use the proposed SDWI method to detect the discrete gross error, the regional gross error and discrete-region gross error in the shipborne gravity, separately. The results show that the detection success rate is 100% and failure rate is 0 for all three kinds of gross errors, better than that of the traditional WTS method. The real data experiment also confirms that the proposed method is effective in detecting gross errors.