A fast non-parametric CFAR ship detector based on the statistical modeling of sea clutter in SAR images is proposed. Typical CFAR detectors, like the double parameter model (DPM), assume a Gaussian sea clutter model and usually degrade the image resolution using target windows. The proposed detector works in a pixel-by-pixel fashion, adaptively selecting a decision threshold for every single patch the SAR image is divided into. Sea clutter is modeled using the Generalized Gamma distribution. Therefore, the presence of different-sized ships will not become an issue and they will be better characterized, allowing the extraction of the target information, which could be used for refocusing, feature extraction, modeling and classification, while maintaining the resolution of the SAR image.