ID 原文 译文
20555 针对被动声呐对宽带干扰抑制的应用需求，该文提出一种利用少快拍数据的宽带干扰鲁棒性抑制算法。 For the requirement of broadband interference suppression for passive sonar, a robust broadband interference suppression algorithm using few snapshots is proposed.
20556 算法基于宽带干扰的预估方位，得到带宽内多频点叠加的导向互谱密度矩阵，以此估计出信号子空间，并采用投影法对单位向量修正，再逆转换得到干扰导引向量估计。 Based on the estimated bearing of thebroadband interference, the algorithm obtains the steered cross-spectral density matrix through multi-frequencydata in the bandwidth and estimates the signal subspace, then uses the projection approach to correct the unitvector, and estimates the steering vector of interference through inversely transforming.
20557 对所有待抑制的干扰重复上述步骤，得到干扰导引向量集，进而构造抑制矩阵。 Repeating above stepscan obtain the interference steering vector set, thereby constructing the suppression matrix.
20558 对阵元域数据处理得到剔除掉干扰成分的阵元数据，再进行空间处理即可得到最终的空间谱。 The interference component of array data is eliminated by suppression matrix processing, and the final spatial spectrum can be obtained after spatial processing.
20559 理论分析及仿真、海试数据处理表明，算法可采用少快拍，甚至单快拍的频域数据进行处理。在目标运动、环境状态快速变化等不适宜时间积分的环境下依然具有良好性能，同时对空间处理面临的各类失配具有鲁棒性。 The theoretical analysis, simulation and processing of sea trial data show that the proposed algorithm uses few, even single frequency domain snapshots processing, and still has good performance in environments where target motion, conditions rapid change and other conditions that time integration is unsuitable, at the same time, algorithm is robust for mismatches faced by space processing.
20560 基于CFAR和核密度估计(KDE)的SAR传统舰船候选区域提取方法存在以下缺陷： The traditional methods based on CFAR and Kernel Density Estimation (KDE) for SAR shipcandidate region extraction has the following defects:
20561 CFAR虚警率依赖人工经验选择；CFAR仅对杂波分布建模，会对被检目标构成一定的漏检风险； The choice of false alarm rate of CFAR depends on artificial experience; CFAR only models the sea clutter distribution, which poses a certain risk of missing detection to the target;
20562 利用KDE进行强海杂波过滤时，需凭人工经验选择滤除阈值。 When KDE is used to filter strong sea clutter, the threshold must be selected by artificial experience.
20563 这使得传统舰船候选区域提取方法无法适应多星多分辨率等复杂场景。 These defects make the traditional method unable to adapt to complex scene, such asmulti-satellite and multi-resolution.
20564 该文提出一种面向多星多分辨率的SAR图像舰船候选区域提取算法， A candidate region extraction method for multi-satellite and multi-resolution SAR ships is proposed.