Weak Target Detection Based on EMD and Hurst Exponent

Sea-surface weak target detection based on fractal characteristics has drawn intensive attentions in radar community recent years. However, the fractal differences between target and sea clutter are not probably significant due to the fact that target echo has been corrupted by clutter. The time-frequency distribution generated by Hilbert-Huang transform (HHT) indicates that the spectrum of target echo is mainly distributed near zero frequency, which is different from the spectrum of sea clutter. In order to enhance the difference of fractal characteristics between target and clutter, this paper applies Empirical Mode Decomposition (EMD), the first procedure of HHT, to extract the lower frequency components of radar raw echo. Then, Hurst exponent is used to construct the fractal detector. Simulation results using real data show that the performance of this new algorithm is better than the raw data-based Hurst-exponent method and the EMD-based box-dimension method.