Detection of low observable targets within sea clutter by structure function based multifractal analysis

Sea clutter is the backscattered returns from a patch of the sea surface illuminated by a radar pulse. Robust detection of targets within sea clutter may strengthen coastal security, improve navigation safety, and help environmental monitoring. However, no simple and reliable methods for detecting targets within sea clutter have been proposed. We introduce the structure function based multifractal theory to analyze 392 sea clutter datasets measured under various sea and weather conditions. It is found that sea clutter data exhibit multifractal behaviors in the time scale range of about 0.01 s to a few seconds, especially for data with targets. The fractal and multifractal features of sea clutter enable us to develop a simple and effective method to detect targets within sea clutter. It is shown that the method achieves very high detection accuracy. It is further shown that in the time scale range of 0.01 s to a few seconds, sea clutter data is weakly nonstationary. The nonstationarity may explain why modeling using distributions such as Weibull, log-normal, K, and compound-Gaussian only offers limited understanding of the physics of sea clutter and is not very effective in detecting targets within sea clutter.