Ship detection method for single-polarization synthetic aperture radar imagery based on target enhancement and nonparametric clutter estimation

Ship detection with synthetic aperture radar (SAR) imagery often confronts severe speckle, heterogeneous regions, and system noise which cause false alarms due to the faint ship-sea contrast. Additionally, false negatives also occur when small vessels with low radar back-scatter are observed. To solve these problems, a new ship detection method based on target enhancement and nonparametric clutter estimation is proposed. The method not only improves the ship-sea contrast for homogeneous and nonhomogeneous images but also adaptively estimates the clutter distribution in the enhanced image, which is crucial for the constant false-alarm rate (CFAR) detector. Subsequently, ships in the SAR image are detected by the proposed two-stage kernel density estimation CFAR (KDE-CFAR) with a low false-alarm rate and high detection probability. Compared with most existing algorithms, the proposed method provides a robust detection capability for both homogeneous and nonhomogeneous SAR images. Experimental results also reveal that the proposed method is an effective method for ship detection in various Radarsat-1 and Envisat ASAR images acquired with different operation modes. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)