ID 原文 译文
1503 在已有的极化合成孔径雷达(PolSAR)图像恒虚警(CFAR)检测方法中，存在着高分辨下杂波模型适用性差的难题。 There is a problem of the poor applicability of clutter models under high resolution with the existing con-stant false alarm rate (CFAR)detection methods in polarimetric synthetic aperture radar (PolSAR)imageries.
1504 为此提出了一种 Fisher 分布下的 CFAR 检测方法，并定义虚警损失率(CFAR Loss，CL)以量化评估算法的恒虚警保持性能。 To solve the problem, a CFAR detection method is proposed under Fisher texture, and the CFAR loss (CL)is defined to quantitatively e-valuate the CFAR maintenance performance of detection methods.
1505 首先，在乘积模型框架下引入 Fisher 纹理变量，推导出了多视极化匹配滤波(Multi-look PolarizationMatched Filter，MPMF)检测量的概率密度函数(PDF)。 Firstly, the probability density function (PDF)of themulti-look polarization matched filter (MPMF)metric is derived based on product model combining the hypothesis of theFisher texture.
1506 然后，对 PDF 积分得到了虚警概率的闭合解析式，并设计了CFAR 检测流程。 Secondly, the PDF of the MPMF metric is integrated, and the analytical expression of the false alarm rate isobtained.
1507 仿真数据和机载合成孔径雷达(Airborne SAR，AIRSAR)数据实验结果表明，与基于 K 分布、G0分布、Wishart 分布的 CFAR 检测算法以及双参数恒虚警(two-Parameter CFAR，2P-CFAR)算法相比，新方法具有良好的恒虚警保持性能和检测性能，具有较强的鲁棒性，且运算时间未明显增加， The process of the proposed CFAR detection method is also designed. Compared with other methods based on K, G0and Wishart distribution, as well as the two-parameter CFAR (2P-CFAR)detector via simulation data and airborne SAR(AIRSAR)data, the proposed method has good constant false alarm maintenance performance and detection performance, strong robustness and no significant increase in operation time.
1508 相比于其他检测方法，品质因数(Figure of Merit，FoM)平均高出 12.80% 。 Compared with other detection methods, the figure of merit(FoM)is 12. 80% higher on average.
1509 路径覆盖是软件测试领域重要的测试方法之一。 Path coverage is one of the most important testing methods in the field of software testing.
1510 在搜索空间中，找到一组测试数据满足路径覆盖是一个具有挑战性的问题。 It is a challeng-ing problem to find a set of test data to satisfy the path coverage in the search space.
1511 因此，自动生成测试数据是软件测试的关键问题。 Therefore, automatically generating testdata is a key issue in software testing.
1512 文中提出一种基于否定选择遗传算法的路径覆盖测试数据生成方法，将否定选择策略融入遗传算法，动态优化遗传算法的种群数据，自动生成覆盖目标路径的测试数据。 In this paper, a generation method of test data based on the negative selection geneticalgorithm is proposed. The negative selection strategy is integrated into the genetic algorithm, and the population data of thegenetic algorithm is dynamically optimized, and the test data covering the target path is automatically generated.