...
首页> 外文期刊>Radar, Sonar & Navigation, IET >Floating small target detection in sea clutter via normalised Doppler power spectrum
【24h】

Floating small target detection in sea clutter via normalised Doppler power spectrum

机译:归一化多普勒功率谱检测海杂波中的小目标

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

This paper, proposes a detector based upon normalised Doppler power spectrum (NDPS) is proposed to find floating small targets in sea clutter. Doppler power spectra (DPS) of sea clutter are modelled by a positive stochastic process in Doppler bins. To measure the power fluctuation of sea clutter at each Doppler bin, the NDPS is constructed which equals the DPS of the received time series subtracting the mean function and divided by the standard deviation function of the stochastic process. In view of the Doppler spread when the target return power is integrated within a long observation time, a double detection scheme is developed. The NDPS at the cell under test (CUT) is first estimated from the DPS at the reference range cells and CUT. Then, the first-stage detection is conducted by the shape-parameter-dependent thresholds to yield the thresholded NDPS at individual Doppler bins. The second-stage detection is made by selective integration of the thresholded NDPS. The proposed detector is compared with the fractal-based and tri-feature-based detectors by using the real high-resolution sea clutter datasets. The experimental results show that the proposed detector attains better performance than the fractal-based detector and has comparable performance with the tri-feature-based detector but lower computational complexity.
机译:本文提出了一种基于归一化多普勒功率谱(NDPS)的探测器,用于寻找海杂波中的漂浮小目标。海杂波的多普勒功率谱(DPS)通过多普勒箱中的正随机过程进行建模。为了测量每个多普勒频点处海杂波的功率波动,构建了NDPS等于接收到的时间序列的DPS减去均值函数并除以随机过程的标准偏差函数。考虑到当目标返回功率在很长的观察时间内被积分时的多普勒扩展,开发了一种双重检测方案。首先根据参考范围像元和CUT处的DPS估算被测像元(CUT)处的NDPS。然后,通过形状参数相关阈值进行第一阶段检测,以在各个多普勒频点处生成阈值NDPS。第二阶段检测是通过对阈值NDPS进行选择性积分来进行的。通过使用真实的高分辨率海杂波数据集,将提出的探测器与基于分形和基于三特征的探测器进行比较。实验结果表明,所提出的检测器具有比基于分形的检测器更好的性能,并且与基于三特征的检测器具有可比的性能,但计算复杂度较低。

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