ATDI-Group/AST_finetuned_SIGIDwiki

Audio Spectrogram Transformer finetuned on SIGID wiki for Radio Signal Classification

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on radio signal recordings documented in SIGID wiki. It was built by ATDI's AI team to provide a base model for radio signal classification.

It achieves the following results on the evaluation set:

• Accuracy: 0.99
• Validation Loss: 0.05

Dataset

We built our own dataset using SIGID wiki. The model is trained to recognize the following radio systems:

• 4G LTE Network
• 5G "New Radio" cellular network - Downlink
• Aircraft Communications Addressing and Reporting System (ACARS)
• Amplitude Modulation (AM)
• Automatic Identification System (AIS)
• Automatic Link Set-up (ALIS)
• Automatic Picture Transmission (APT)
• Bluetooth
• Differential Global Positioning System (DGPS)
• Digital Audio Broadcasting Plus (DAB+)
• Digital Mobile Radio (DMR)
• Digital Video Broadcasting — Terrestrial (DVB-T)
• High Frequency Data Link (HFDL)
• Instrument Landing System
• M20 Radiosonde
• Morse Code (CW)
• Non-Directional Beacon (NDB)
• Radar altimeter
• STANAG 5065
• Secondary surveillance radar (SSR)
• Single Sideband Voice
• Tetrapol
• VHF Data Link - Mode 2 (VDL-M2)
• VHF Omnidirectional Range (VOR)

Usage

You can use the raw model for classifying signals into one of the SIGID wiki classes specified above and in config.json. You can also fine-tune this model on your own radio signal dataset to make it more specific.