# Doppler-Resilient 802.11ad-Based Ultra-Short Range Automotive Joint Radar-Communications System

arXiv: https://arxiv.org/abs/1902.01306 · HTML: https://mlsanity.com/paper/1902.01306/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2019.

## Built on by (most cited first, 5 of 5)

- [Radars for Autonomous Driving: A Review of Deep Learning Methods and Challenges](https://mlsanity.com/paper/2306.09304/) (2023)
- [Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model](https://mlsanity.com/paper/2104.10378/) (2021)
- [Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming](https://mlsanity.com/paper/2103.00328/) (2021)
- [Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications](https://mlsanity.com/paper/2211.09253/) (2022)
- [Redefining Automotive Radar Imaging: A Domain-Informed 1D Deep Learning Approach for High-Resolution and Efficient Performance](https://mlsanity.com/paper/2406.07399/) (2024)

## Abstract (arXiv)

We present an ultra-short range IEEE 802.11ad-based automotive joint radar-communications (JRC) framework, wherein we improve the radar's Doppler resilience by incorporating Prouhet-Thue-Morse sequences in the preamble. The proposed processing reveals detailed micro-features of common automotive objects verified through extended scattering center models of animated pedestrian, bicycle, and car targets. Numerical experiments demonstrate 2.5% reduction in the probability-of-false-alarm at low signal-to-noise-ratios and improvement in the peak-to-sidelobe level dynamic range up to Doppler velocities of ±144 km/hr over conventional 802.11ad JRC.