首个公开的合成雷达脉冲数据集，助力电子战脉冲解交织研究
The Turing Synthetic Radar Dataset: A dataset for pulse deinterleaving
- 基于仿真生成6000个脉冲序列，模拟最多110个发射源的复杂场景
- 包含近30亿个脉冲，支持高密度参数重叠下的解交织任务
- 配套挑战赛推动标准化评估，适合雷达信号处理与电子战研究者
我们提出图灵合成雷达数据集，一个全面的数据集，既可作为雷达脉冲解交织研究的基准，也可推动新方法的发展。该数据集解决电子战与信号情报中的关键问题：从多个未知发射源中分离交错的雷达脉冲。数据集包含6000个脉冲序列，覆盖两种接收配置，总计近30亿个脉冲，涵盖最多110个发射源、显著的参数空间重叠等真实场景。为促进数据集使用并建立标准化评估流程，我们启动了配套的图灵解交织挑战赛，要求模型通过聚类将交错脉冲序列中的脉冲正确关联到对应发射源，并最大化V-measure等指标。该数据集是电子战领域首批公开、全面仿真的脉冲序列数据集之一，旨在推动复杂模型的研发。
原文摘要 · Abstract (English)
We present the Turing Synthetic Radar Dataset, a comprehensive dataset to serve both as a benchmark for radar pulse deinterleaving research and as an enabler of new research methods. The dataset addresses the critical problem of separating interleaved radar pulses from multiple unknown emitters for electronic warfare applications and signal intelligence. Our dataset contains a total of 6000 pulse trains over two receiver configurations, totalling to almost 3 billion pulses, featuring realistic scenarios with up to 110 emitters and significant parameter space overlap. To encourage dataset adoption and establish standardised evaluation procedures, we have launched an accompanying Turing Deinterleaving Challenge, for which models need to associate pulses in interleaved pulse trains to the correct emitter by clustering and maximising metrics such as the V-measure. The Turing Synthetic Radar Dataset is one of the first publicly available, comprehensively simulated pulse train datasets aimed to facilitate sophisticated model development in the electronic warfare community
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