Detection and identification of emitters provide vital information for defensive strategies in electronic intelligence. Based on a received signal containing pulses from an unknown number of emitters, this paper introduces an unsupervised methodology for deinterleaving RADAR signals based on a combination of clustering algorithms and optimal transport distances. The first step involves separating the pulses with a clustering algorithm under the constraint that the pulses of two different emitters cannot belong to the same cluster. Then, as the emitters exhibit complex behavior and can be represented by several clusters, we propose a hierarchical clustering algorithm based on an optimal transport distance to merge these clusters. A variant is also developed, capable of handling more complex signals. Finally, the proposed methodology is evaluated on simulated data provided through a realistic simulator. Results show that the proposed methods are capable of deinterleaving complex RADAR signals.

翻译：摘要： 辐射源的检测与识别为电子情报中的防御策略提供了关键信息。针对包含未知数量辐射源脉冲的接收信号，本文提出了一种结合聚类算法与最优传输距离的无监督雷达信号去交错方法。第一步，在确保不同辐射源脉冲不属于同一聚类的约束条件下，利用聚类算法对脉冲进行分离。随后，鉴于辐射源会呈现复杂行为且可能由多个聚类表示，我们提出了一种基于最优传输距离的层次聚类算法来合并这些聚类。此外，还开发了一种能处理更复杂信号的改进变体。最后，通过真实模拟器生成的仿真数据对所提方法进行验证。结果表明，该方法能够有效实现复杂雷达信号的去交错。