...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Detection of a Low Observable Sea-Surface Target With Micromotion via the Radon-Linear Canonical Transform
【24h】

Detection of a Low Observable Sea-Surface Target With Micromotion via the Radon-Linear Canonical Transform

机译：通过the线性正则变换利用微运动检测低可观测的海面目标

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this letter, a novel long-time coherent integration method, known as the Radon-linear canonical transform (RLCT), is proposed for detection of a low observable moving target in sea clutter. The micro-Doppler (m-D) of a sea-surface target is studied and modeled as multiple linear-frequency-modulated signals, which result from the accelerated and 3-D rotated movements. The RLCT-based algorithm employs m-D as a useful signature for target detection and can simultaneously compensate the range and Doppler migrations during long observation time, which simplifies the operational procedure. By searching along the moving trajectory and using extra three degrees of freedom, the observation values of m-D signals can be well matched and accumulated as peaks in the RLCT domain. Then, the target can be declared by comparing the peak value with an adaptive threshold. The definition of the RLCT demonstrates that it is the generalization of the popular moving target detection, Radon-Fourier transform, fractional Fourier transform, and linear canonical transform methods. Finally, experiments using a real sea clutter data set show that the proposed method can achieve high integration gain and detection probability of a micromotion target in heavy sea clutter.
机译：在这封信中，提出了一种新颖的长期相干积分方法，称为Radon线性规范变换（RLCT），用于检测海杂波中的低可观测运动目标。对海面目标的微多普勒（m-D）进行了研究，并建模为多个线性频率调制信号，这些信号是由加速运动和3-D旋转运动产生的。基于RLCT的算法将m-D用作目标检测的有用签名，并且可以在较长的观察时间内同时补偿距离和多普勒偏移，从而简化了操作过程。通过沿移动轨迹搜索并使用额外的三个自由度，m-D信号的观测值可以很好地匹配并作为RLCT域中的峰值进行累积。然后，可以通过将峰值与自适应阈值进行比较来声明目标。 RLCT的定义表明，它是流行的移动目标检测，Radon-Fourier变换，分数阶Fourier变换和线性规范变换方法的推广。最后，利用真实海杂波数据集进行的实验表明，该方法可以在海杂波中获得较高的积分增益和微运动目标的检测概率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号