# The Turing Synthetic Radar Dataset: A dataset for pulse deinterleaving

arXiv: https://arxiv.org/abs/2602.03856 · HTML: https://mlsanity.com/paper/2602.03856/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 12 references that are in the map.
- First posted on arXiv 23 Jan 2026.

## Builds on (most cited first, 6 of 6)

- [Over the Air Deep Learning Based Radio Signal Classification](https://mlsanity.com/paper/1712.04578/) (2017)
- [Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification](https://mlsanity.com/paper/2101.10254/) (2021)
- [Multi-task Learning for Radar Signal Characterisation](https://mlsanity.com/paper/2306.13105/) (2023)
- [Multi-stage Learning for Radar Pulse Activity Segmentation](https://mlsanity.com/paper/2312.09489/) (2023)
- [LSTM Framework for Classification of Radar and Communications Signals](https://mlsanity.com/paper/2305.03192/) (2023)
- [Radar Pulse Deinterleaving with Transformer Based Deep Metric Learning](https://mlsanity.com/paper/2503.13476/) (2025)

## Built on by (most cited first, 1 of 1)

- [Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving](https://mlsanity.com/paper/2609.25057/) (2026)

## Abstract (arXiv)

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