首页> 外文会议>IEEE Radar Conference >When Should We Use Likelihood Ratio Target Detection with QTMS Radar and Noise Radar?
【24h】

When Should We Use Likelihood Ratio Target Detection with QTMS Radar and Noise Radar?

机译:我们应该什么时候使用QTM雷达和噪声雷达的似然比目标检测?

获取原文

摘要

We analyze the potential application of a generalized likelihood ratio (GLR)-based detector function to quantum two-mode squeezing (QTMS) radars and standard noise radars. We give an expression for the likelihood ratio (LR) in terms of the maximum-likelihood estimate of the correlation coefficient between the received and reference signals of the radar. Interestingly, we found that a previously-studied detector function outperforms the GLR detector, though not in all parameter regimes. This runs counter to the intuition, based on the Neyman-Pearson lemma, that the LR test is optimal. We discuss why the lemma does not hold in this particular case and why the search for detector functions for QTMS radars and noise radars remains open. However, the GLR detector is a good choice when the correlation coefficient is high, the number of integrated samples is low, and appropriate computational resources are available.
机译:我们分析了广义似然比(GLR)的探测器函数对量子两模挤压(QTMS)雷达和标准噪声雷达的潜在应用。 我们在雷达的接收和参考信号之间的相关系数的最大似然估计方面给出了似然比(LR)的表达。 有趣的是,我们发现先前研究的探测器函数优于GLR探测器,但在所有参数制度中都没有。 基于Neyman-Pearson Lemma,这与Intuition相反,LR测试是最佳的。 我们讨论了为什么引理在这个特殊情况下没有持有,为什么搜索QTM雷达和噪声雷达的检测器功能仍然是打开的。 但是,当相关系数高时,GLR检测器是一个不错的选择,集成样本的数量低,并且可以使用适当的计算资源。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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