论文标题
基于QTMS雷达和噪声雷达的基于似然比的检测器
A Likelihood Ratio-Based Detector for QTMS Radar and Noise Radar
论文作者
论文摘要
我们得出基于使用可能性比（LR）测试来区分目标和不存在目标的量子两模式挤压（QTM）雷达（QTM）雷达和噪声雷达的检测器函数。除了对LR检测器的显式表达式外，我们还得出一个检测器函数，该函数近似于LR检测器的限制，而目标范围很小，远处或其他难以检测。当集成样品的数量较大时，我们将在使用LR检测器时得出雷达接收器工作特性（ROC）曲线的理论表达。当样品数量很少时，我们使用模拟来了解检测器的ROC曲线行为。一个有趣的发现是存在一个参数制度，在该方案中，先前研究的检测器的表现优于LR检测器，这与直觉是LR测试是最佳的。这是因为Neyman-Pearson的引理和概括引理的Karlin-Rubin定理都没有在这个特定的问题中。但是，LR检测器仍然是目标检测的好选择。
We derive a detector function for quantum two-mode squeezing (QTMS) radars and noise radars that is based on the use of a likelihood ratio (LR) test for distinguishing between the presence and absence of a target. In addition to an explicit expression for the LR detector, we derive a detector function which approximates the LR detector in the limit where the target is small, far away, or otherwise difficult to detect. When the number of integrated samples is large, we derive a theoretical expression for the receiver operating characteristic (ROC) curve of the radar when the LR detector is used. When the number of samples is small, we use simulations to understand the ROC curve behavior of the detector. One interesting finding is there exists a parameter regime in which a previously-studied detector outperforms the LR detector, contrary to the intuition that LR tests are optimal. This is because neither the Neyman-Pearson lemma, nor the Karlin-Rubin theorem which generalizes the lemma, hold in this particular problem. However, the LR detector remains a good choice for target detection.
