An optimized atmospheric missed data recovery algorithm based on singular spectrum iteration

A new idea of interval quartering algorithm was proposed to improve the insufficiency of the conventional singular spectrum analysis iterative interpolation on parameter selection (including the number K of principal component and the embedding dimension M), and the applied test and comparative analysis recovery was carried out to the missing data. The experimental results showed that the improved method is very effective to the interpolation of missing data, and the computing speed of the improved algorithm is more rapid than that of conventional algorithm.