使用径向基函数耦合映射格子进行信号检测。

Signal detection using the radial basis function coupled map lattice.

作者信息

Leung H, Hennessey G, Drosopoulos A

机构信息

Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada.

出版信息

IEEE Trans Neural Netw. 2000;11(5):1133-51. doi: 10.1109/72.870045.

DOI:10.1109/72.870045

PMID:18249840

Abstract

Conventional detection methods used in current marine radar systems do not perform efficiently in detecting small targets embedded in a clutter environment. Based on a recent observation that sea clutter, radar echoes from a sea surface, is chaotic rather than random, we propose using a spatial temporal predictor to reconstruct the chaotic dynamic of sea clutter because electromagnetic wave scattering is a spatial temporal phenomenon which is physically modeled by partial differential equations. The spatial temporal predictor used here is called radial basis function coupled map lattice (RBF-CML) which uses a linear combiner to fuse either measurements in different spatial domains for an RBF prediction or predictions from several RBF nets operated on different spatial regions. Using real-life radar data, it is shown that the RBF-CML is an effective method to reconstruct the sea clutter dynamic. The RBF-CML predictor is then applied to detect small targets in sea clutter using the constant false alarm rate (CFAR) principle. The spatial temporal approach is shown, both theoretically and experimentally, to be superior to a conventional CFAR detector.

摘要

当前海洋雷达系统中使用的传统检测方法在检测杂波环境中的小目标时效率不高。基于最近的一项观察，即海杂波（海面的雷达回波）是混沌的而非随机的，我们建议使用时空预测器来重构海杂波的混沌动态，因为电磁波散射是一种时空现象，由偏微分方程进行物理建模。这里使用的时空预测器称为径向基函数耦合映射格子（RBF-CML），它使用线性组合器来融合不同空间域中的测量值以进行RBF预测，或者融合在不同空间区域上运行的多个RBF网络的预测结果。利用实际雷达数据表明，RBF-CML是重构海杂波动态的有效方法。然后，基于恒虚警率（CFAR）原理，将RBF-CML预测器应用于检测海杂波中的小目标。理论和实验均表明，时空方法优于传统的CFAR检测器。