Extended fractal analysis for floating target detection in sea clutter

In this paper, the amplitude time series of sea clutter are described by the extended self-similar (ESS) process and the extended fractal (EF) feature of real-life radar datasets is evaluated. Different from the fractal description of sea clutter by fractal dimension or Hurst parameter at a finite scale range, the EF feature can characterize the roughness of the clutter at different scales by a series of multiscale Hurst parameters. A detail analysis of real-life sea clutter time series is made by multiscale Hurst parameters, which expose the dominating factor at three specific scale ranges. A detector via multiscale Hurst parameter is proposed to detect the floating target in sea clutter and the performance is verified by real-life IPIX radar datasets.