利用香农熵的双极化合成孔径雷达船只检测

摘要

The traditional constant false alarm rate (CFAR)ship detection methods have poor automaticity,and it is difficult to set false alarm rate.According to the principle that shannon entropy shows different features for ship and sea,we present a new ship detection algorithm based on shannon entropy.To test the detection performance of the new method,eight scenes of C band Radarsat-2 dual-polarimetric SAR test data were used.The algorithm of K-CFAR,G0-CFAR and XC ship detection algorithm based on reflection symmetry were contrastively analyzed with the new method for ship detection.The experimental results demonstrate that the new method has preferable detection performance.%针对传统恒虚警率（CFAR）船只目标检测方法存在虚警率设置困难、算法自动性差的问题，该文结合香农熵特征对于船只目标和海面表现出不同特性的原理，即船只目标的香农熵为正值，海面的香农熵为负值，提出了一种基于香农熵的船只目标检测方法。文中利用8景 C 波段 Radarsat-2双极化 SAR 数据进行检验，与 K-CFAR、G0-CFAR 及基于反射对称性的 XC 船只目标检测算法进行对比分析，结果表明本文提出的方法具有较好的检测性能。