license: mit
pretty_name: FARM Aerial Radio Map Dataset
task_categories:
- image-to-image
- feature-extraction
tags:
- radio-map
- aerial-networking
- wireless-communication
- low-altitude-networking
- foundation-model
- simulation
size_categories:
- 10M<n<100M
FARM Aerial Radio Map (ARM) Dataset
Paper:
- FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking (https://arxiv.org/abs/2604.17362)
Overview
This repository releases the constructed ARM datasets based on ARM-Omni for FARM training, in-domain evaluation (D1-D10), and zero-shot evaluation (P1, F1, and A1). The dataset coverage is summarized below:
| Dataset | Frequencies (GHz) | Max Rx Height (m) | Beamwidths | Map Grid Size | Volume |
|---|---|---|---|---|---|
| D1 | 2.1, 3.3, 5.9 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D2 | 3.5, 4.9, 5.9 | 130 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D3 | 2.1, 4.9, 5.9 | 110 | 30°, 120° | 512 × 512 | 15000 |
| D4 | 3.3, 3.5, 4.9 | 110 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D5 | 3.3, 4.9, 5.9 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D6 | 2.1, 3.3, 3.5 | 130 | 30°, 120° | 512 × 512 | 15000 |
| D7 | 2.1, 3.3, 3.5, 5.9 | 130 | 30°, Iso | 512 × 512 | 15000 |
| D8 | 2.1, 3.5, 4.9, 5.9 | 100 | 120°, Iso | 512 × 512 | 15000 |
| D9 | 2.1, 3.3, 3.5, 4.9 | 120 | 30°, 120° | 512 × 512 | 15000 |
| D10 | 2.1, 3.3, 3.5, 4.9, 5.9 | 130 | 30°, 120°, Iso | 512 × 512 | 15000 |
| P1 | 2.1, 3.3, 3.5, 4.9, 5.9 | 150 | 30°, 120°, Iso | 256 × 256 | 15000 |
| F1 | 2.6, 7.1 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| A1 | 2.1, 3.3, 3.5, 4.9, 5.9 | 120 | 60° | 512 × 512 | 15000 |
A fuller ARM-Omni release is planned for a future update.
Repository Layout
Each scene is stored as a compressed archive on the Hub:
<dataset>/scene_<scene_id>.tar.gz
After extraction, the scene contains .npy ARM tensors organized as:
<dataset>/<scene_id>/<frequency>/<antenna_pattern>/tx<ID>_yaw<VALUE>.npy
Example:
D1/7/freq59/iso/tx45_yaw0.npy
Scene IDs are not globally continuous across dataset groups. Users should rely on the extracted folder names as the authoritative scene IDs.
Data Format
Each released raw .npy file stores an ARM volume with shape:
1 × 30 × 512 × 512
The dimensions correspond to one radio-map channel, 30 height layers, and a 512 × 512 spatial grid. During data loading, different input sizes can be obtained by selecting a subset of height layers and applying a spatial crop centered on the transmitter pixel. For example, this procedure is used to obtain the 256 × 256 crop for P1.
Signal Encoding and Scene Metadata
- The no-signal truncation threshold is
-120 dB. In the encodeduint8representation, this threshold corresponds to pixel value130. - Building occupancy is embedded in the released ARM tensors; in each height-layer radio map, pixels with value
0correspond to building-occupied regions. - The transmitter location metadata is stored in the scene-level CSV file:
<dataset>/<scene_id>/tx_positions_512.csv
## Citation
If you use this dataset, please cite our paper:
```text
S. Gao, J. Liang, Y. Yuan, W. Lu, G. Shen, and L. Yang, "FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking," arXiv preprint arXiv:2604.17362, 2026.
@article{gao2026farm,
author = {Gao, Shijian and Liang, Jiahui and Yuan, Yifeng and Lu, Wenlihan and Shen, Guobin and Yang, Liuqing},
title = {{FARM}: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking},
journal = {arXiv preprint arXiv:2604.17362},
year = {2026}
}