A Complex Modal Local Mean Decomposition Method
Yuanduo Niu, Qianqiang Lin, Haoran Du, Jianying Tian · 2024
Targets with rotating components generate micro-motion modulation components in addition to the main components. However, extracting parameters related to the rotating components is often hindered by the interference of strong main components, making it challenging to obtain accurate target parameters directly from radar received echo signals. To address the issue of mixing rotating component components in the main components during the separation process, a method called Complex Mode Local Mean Decomposition (CMLMD) is proposed. In comparison to Complex Empirical Mode Decomposition (CEMD) and Complex Local Mean Decomposition (CLMD) methods, the CMLMD method excels in handling the local characteristics and modal decomposition of signals, resulting in more accurate local mean values and modal functions, thereby achieving better decomposition results and facilitating a deeper understanding and analysis of signal characteristics. The CMLMD method first obtains the average envelope function through interpolation, identifies Intrinsic Mode Function (IMF) components based on a threshold criterion, and then decomposes the IMF components using Local Mean Decomposition (LMD). The separation process is determined to be complete based on whether the result is a pure frequency modulation signal. Simulation experiments demonstrate that the decomposition performance of CMLMD outperforms that of CEMD and CLMD methods, achieving an accuracy rate of up to 97.20%• The method exhibits minimal fluctuation in performance with changes in signal-to-noise ratio, indicating good robustness. Validation with real-world data further confirms the effectiveness of the proposed method in radar signal processing.