首页> 外文OA文献 >Non-cooperative identification of civil aircraft using a generalised mutual subspace method
【2h】

Non-cooperative identification of civil aircraft using a generalised mutual subspace method

机译:使用广义互子空间法的民航非合作识别

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The subspace-based methods are effectively applied to classify sets of feature vectors by modelling them asudsubspaces. However, their application to the field of non-cooperative target identification of flying aircraft is barely seen in the literature. In these methods, setting the subspace dimensionality is always an issue. Here, it is demonstrated that a modified mutual subspace method, which uses softweights to set the importance of each subspace basis, is a promising classifier for identifying sets of range profiles coming from real in-flight targets with no need to set the subspace dimensionality in advance. The assembly of a recognition database is also a challenging task.udIn this study, this database comprises predicted range profiles coming from electromagnetic simulations. Even though the predicted and actual profiles differ, the high recognition rates achieved reveal that the algorithm might be a good candidate for its application in an operational target recognition system.
机译:通过将子向量建模为 udsubspace,可将基于子空间的方法有效地用于对特征向量集进行分类。然而,它们在飞行器非合作目标识别领域的应用在文献中几乎看不到。在这些方法中,设置子空间维数始终是一个问题。在这里,证明了一种改进的相互子空间方法,该方法使用软加权来设置每个子空间基础的重要性,是一种很有希望的分类器,用于识别来自真实飞行目标的距离轮廓集,而无需在其中设置子空间维数。预先。识别数据库的组装也是一项艰巨的任务。 ud在本研究中,该数据库包含来自电磁仿真的预测范围轮廓。即使预测的配置文件和实际的配置文件有所不同,所实现的高识别率也表明该算法可能是其在操作目标识别系统中应用的良好候选者。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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