Natural frequency extraction using late-time evolutionary programming-based CLEAN

In this paper, we present a novel method for natural frequency extraction. Our algorithm is called late-time evolutionary programming (EP)-based CLEAN, and has many advantages compared to conventional methods. The accuracy of our algorithm is not affected by the false estimation of the number of natural resonance modes. Furthermore, our method is insensitive to random noise. Insensitivity is a very important characteristic in the resonance extraction algorithm since the late-time response usually has small energy. Using synthetic data, we show these characteristics by comparing them to Pronyʹs method and the E-pulse technique. We also applied our method to the numerical data and B-52 measured data which is obtained at Michigan State University (MSU) arch range.