Many ship target detection methods have been developed since it was verified that ship could be imaged with the space-based SAR systems. Most developed detection methods mostly emphasized ship detection rate but not computation time. By making use of the advantages of the K-distribution CFAR method and two-parameter CFAR method,a new CFAR ship target detection algorithm was proposed. In that new method,we use the K-distribution CFAR method to calculate a global threshold with a certain false-alarm rate. Then the threshold is applied to the whole SAR imagery to determine the possible ship target pixels,and a binary image is given as the preliminary result. Mathematical morphological filter are used to filter the binary image. After that step,we use the two-parameter CFAR method to detect the ship targets. In the step,the local sliding window only works in the possible ship target pixels of the SAR imagery. That step avoids the statistical calculation of the background pixels,so the method proposed can much improve the processing speed. In order to test the new method,two SAR imagery with different background were used,and the detection result shows that that method can work well in different background circumstances with high detection rate. Moreover,a synchronous ship detection experiment was carried out in Qingdao port in October 28,2005 to verify the new method and one ENVISAT ASAR imagery was acquired to detect ship targets. It can be concluded from the experiment that the new method not only has high detection rate,but also is time-consuming,and is suitable for the operational ship detection system. Many ship target detection methods have been developed since it was verified that ship could be imaged with the space-based SAR systems. Most developed detection methods have not yet computational time. By making use of the advantages of the K-distribution In that new method, we use the K-distribution CFAR method to calculate a global threshold with a certain false-alarm rate. Then the threshold is applied After the step, we use the two-parameter CFAR method to detect the ship targets. In the step, the local sliding window only works in the possible ship target pixels of the SAR imagery. That step avoids the statistical calculation of the background pixels, so the meth od 拟 can much improve the processing speed. In order to test the new method, two SAR imagery with different background were used, and the detection result shows that that method can work well in different background circumstances with high detection rate. Moreover, a synchronous ship detection experiment was carried out in Qingdao port in October 28, 2005 to verify the new method and one ENVISAT ASAR imagery was acquired to detect ship targets. It can be concluded from the experiment that the new method not only has high detection rate, but also is time-consuming, and is suitable for the operational ship detection system.