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用于改善海洋和风力发电场杂波环境下无源雷达性能的自适应波束形成方法

Adaptive Beamforming Approaches to Improve Passive Radar Performance in Sea and Wind Farms' Clutter.

作者信息

Rosado-Sanz Javier, Jarabo-Amores María Pilar, De la Mata-Moya David, Rey-Maestre Nerea

机构信息

Signal Theory and Communications Department, University of Alcalá, 28801 Alcalá de Henares, Spain.

出版信息

Sensors (Basel). 2022 Sep 10;22(18):6865. doi: 10.3390/s22186865.

Abstract

This article presents the problem of passive radar vessel detection in a real coastal scenario in the presence of sea and wind farms' clutter, which are characterised by high spatial and time variability due to the influence of weather conditions. Deterministic and adaptive beamforming techniques are proposed and evaluated using real data. Key points such as interference localisation and characterisation are tackled in the passive bistatic scenario with omnidirectional illuminators that critically increase the area of potential clutter sources to areas far from the surveillance area. Adaptive beamforming approaches provide significant Signal-to-Interference improvements and important radar coverage improvements. In the presented case study, an aerial target is detected 28 km far from the passive radar receiver, fulfilling highly demanding performance requirements.

摘要

本文提出了在存在海上和风力发电场杂波的真实沿海场景中进行无源雷达船只检测的问题,由于天气条件的影响,这些杂波具有高度的空间和时间变化性。提出了确定性和自适应波束形成技术,并使用实际数据进行了评估。在具有全向照明器的无源双基地场景中解决了诸如干扰定位和特征描述等关键点,这极大地将潜在杂波源的区域增加到远离监视区域的区域。自适应波束形成方法显著提高了信号干扰比,并大幅改善了雷达覆盖范围。在所呈现的案例研究中,在距离无源雷达接收器28公里处检测到一个空中目标,满足了高要求的性能需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae8c/9500949/777611405a9f/sensors-22-06865-g001.jpg

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