English

MIMO OFDM-Enabled ISAC for Low-Altitude Non-Cooperative UAV Surveillance: A Survey

Signal Processing 2026-04-06 v1

Abstract

The widespread use of unmanned aerial vehicles (UAVs) in low-altitude airspace has raised significant safety and security concerns, motivating the development of reliable non-cooperative UAV surveillance technologies. Integrated sensing and communication (ISAC), enabled by multiple-input multiple-output (MIMO) architectures and orthogonal frequency-division multiplexing (OFDM) waveforms, has emerged as a promising paradigm for leveraging cellular infrastructure to support large-scale sensing without additional hardware deployment. This paper presents the first comprehensive survey dedicated to MIMO OFDM-enabled ISAC for low-altitude non-cooperative UAV surveillance, where the targeted UAVs do not intentionally assist the monitoring system through dedicated signaling or prior coordinate sharing. We first analyze the unique propagation characteristics of low-altitude UAV sensing, including severe clutter, rapid channel variations, and mixed near/far-field effects, and discuss corresponding waveform design principles. We then systematically review existing MIMO OFDM-enabled UAV surveillance techniques along four key dimensions: ISAC system modeling and network optimization, UAV detection and tracking algorithms under single and networked base station (BS) architectures, UAV identification techniques based on micro-Doppler and learning-based approaches, and experimental validations and practical field trials. Subsequently, we summarize open challenges such as sensing under severe clutter and multipath, data scarcity for identification, cooperative multi-BS fusion, and real-world deployment constraints. Finally, we outline promising future research directions toward 5G-Advanced (5G-A) and 6G-enabled low-altitude surveillance systems.

Keywords

Cite

@article{arxiv.2604.02680,
  title  = {MIMO OFDM-Enabled ISAC for Low-Altitude Non-Cooperative UAV Surveillance: A Survey},
  author = {Shiyu Bai and Sijia Li and Cunyi Yin and Wenqiu Qu and Li-Ta Hsu and Yuanwei Liu and Wen-Hua Chen},
  journal= {arXiv preprint arXiv:2604.02680},
  year   = {2026}
}

Comments

24 pages, 5 figures, submitted to IEEE Communications Surveys & Tutorials