Title :
A Parzen-Window-Kernel-Based CFAR Algorithm for Ship Detection in SAR Images
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
fDate :
5/1/2011 12:00:00 AM
Abstract :
This letter proposes a Parzen-window-kernel-based algorithm for ship detection in synthetic aperture radar (SAR) images. First, the data-driving kernel functions of Parzen window are utilized to approximate the histogram of real SAR image, in order to complete the accurate modeling of SAR images. Then, a threshold of global constant false alarm rate is given theoretically, and the numerical solution of the threshold is also derived. The experimental results of the real data of typical targets demonstrate that the algorithm presented is effective.
Keywords :
numerical analysis; object detection; radar detection; radar imaging; synthetic aperture radar; Parzen-window-kernel-based CFAR algorithm; SAR images; numerical solution; ship detection; synthetic aperture radar; Clutter; Computational efficiency; Estimation; Kernel; Marine vehicles; Pixel; Synthetic aperture radar; Parzen window; ship detection; synthetic aperture radar (SAR);
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2010.2090492
