CAJ | 학술논문

文章在大量试验的基础上，发现Rice分布能更好地描述噪声和海况因素引起的船海对比度较低时的SAR图像海杂波这一特性，因此提出了基于该分布的CFAR舰船检测算法。实验中利用30 m分辨率VV极化下的高海况ENVISAT ASAR数据和3 m分辨率HH极化下的高噪声的TerraSAR‐X单视数据。结果表明Rice分布CFAR舰船检测算法可用于高海况和高噪声下的SAR图像，在检测准确率及耗时上也优于传统概率模型CFAR算法。
문장재대량시험적기출상，발현Rice분포능경호지묘술조성화해황인소인기적선해대비도교저시적SAR도상해잡파저일특성，인차제출료기우해분포적CFAR함선검측산법。실험중이용30 m분변솔VV겁화하적고해황ENVISAT ASAR수거화3 m분변솔HH겁화하적고조성적TerraSAR‐X단시수거。결과표명Rice분포CFAR함선검측산법가용우고해황화고조성하적SAR도상，재검측준학솔급모시상야우우전통개솔모형CFAR산법。
It is found that Rice distribution can better describe the properties of sea clutter of the syn‐thetic‐aperture radar (SAR) images caused by noise and sea state .So the constant false alarm rate (CFAR) detection algorithm based on Rice distribution is proposed .In the experiments ,the ENVI‐SAT ASAR data of 30 m resolution and VV polarization under high sea state and SLC TerraSAR‐X data of 3 m resolution and HH polarization under high noise are used to test the algorithm .The re‐sults show that the algorithm proposed in this paper is suitable for the SAR images under high noise and high sea state and its detection accuracy and time are superior to those of traditional algorithms .