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The HF surface wave radar WERA. Part II: Spectral analysis of recorded data

机译:HF表面波雷达WERA。第二部分:记录数据的频谱分析

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This paper covers the second part of the analysis of data recorded by the surface wave (SW) over-the-horizon (OTH) WEllen RAdar (WERA). Data were collected by two WERA systems, on May 13th 2008, during the NURC experiment in the Bay of Brest, France. The principal aim of this work is to provide an accurate characterization of the spectral components of the received signal. Secondly, this information is exploited in order to provide a simple and reliable spectral modeling tool. For this reason, auto-regressive (AR) models, also known as linear prediction (LP) models have been investigated. Our results show that at long distances, when the clutter-to-noise power ratio (CNR) is small, the main components of the spectrum can be reasonably described by an AR(12) model, with a good compromise between accuracy and simplicity. As the CNR increases higher-orders are instead to be preferred.
机译:本文涵盖了由表面波(SW)视场(OTH)WEllen RAdar(WERA)记录的数据分析的第二部分。在法国布列斯特湾举行的NURC实验期间,两个WERA系统于2008年5月13日收集了数据。这项工作的主要目的是提供对接收信号频谱成分的准确表征。其次,利用该信息以提供简单而可靠的光谱建模工具。因此,已经研究了自回归(AR)模型,也称为线性预测(LP)模型。我们的结果表明,在长距离时,当杂波噪声功率比(CNR)较小时,可以通过AR(12)模型合理地描述频谱的主要成分,并且在准确性和简便性之间取得了很好的折衷。随着CNR的增加,高阶取而代之是更可取的。

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