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Methodology to Achieve Accurate Non Cooperative Target Identification Using High Resolution Radar and a Synthetic Database

机译:使用高分辨率雷达和合成数据库实现准确的非合作目标识别的方法

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In the last few years, there is a great interest in developing an identification system capable to make a reliable classification of aircrafts into different groups (friendly, hostile or neutral), Depending on the context in which these systems are deployed, incorrect identification may lead to serious problems, such as fratricide or engagement of civilian aircrafts. Different techniques have been researched to face this problem, but non-cooperative ones have awakened more interest because they do not require aircraft collaboration. Non Cooperative Target Identification (NCTI) using radar is a complex task, mainly due to the fact that a database of possible targets is needed. To populate this database, Radar Cross Section (RCS) predictions produced by computer simulation seem to be the most feasible way to perform this task, since measurements alone cannot cover the vast range of targets, configurations and required aspect angles. These predictions are typically performed in the frequency domain and a specific processing must be done to obtain both High Resolution Range Profiles (HRRPs) and 2D Inverse Synthetic Aperture Radar (2D-ISAR) images. This paper shows a methodology to face the NCTI task, which use both synthetic HRRPs and 2D-ISAR to achieve an accurate identification.
机译:在过去的几年里,在开发一个能够使飞机的可靠分类中的识别系统(友好,敌对或中性)的识别系统有很大兴趣,这取决于这些系统的部署,识别不正确的识别可能导致对严重的问题,如弗罗茨拔利或民用飞机的参与。已经研究了不同的技术来面对这个问题,但非合作的人已经唤醒了更多的兴趣,因为他们不需要飞机合作。使用雷达的非合作目标识别(NCTI)是一个复杂的任务,主要是因为需要可能的目标数据库。要填充此数据库,计算机模拟产生的雷达横截面(RCS)预测似乎是执行此任务的最可行方法,因为单独的测量无法涵盖大量目标,配置和所需的方向角度。这些预测通常在频域中执行,并且必须进行特定处理以获得高分辨率范围轮廓(HRRP)和2D逆合成孔径雷达(2D-ISAR)图像。本文显示了面对NCTI任务的方法,它使用合成HRRP和2D-ISAR来实现准确的识别。

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