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Another raw ADS-B signal dataset with labels, the dataset is captured using a BladeRF2 SDR receiver @ 1090MHz with a sample rate of 10MHz


The dataset contains:
1. We conducted a A 24-hour recording of ADS-B signals at DAB on 1090 MHz with USRP B210 (8 MHz sample rate). In total, we got the signals from more than 130 aircraft.
2. An enhanced gr-adsb, in which each message's digital baseband (I/Q) signals and metadata (flight information) are recorded simultaneously. The output file path can be specified in the property panel of the ADS-B decoder submodule.
3. Our GnuRadio flow for signal reception.
4. Matlab code of the paper, wireless device identification using the zero-bias neural network.


1. The "main.m" in Matlab code is the entry of simulation.
2. The "csv2mat" is a CPP program to convert raw records ( of our gr-adsb into matlab manipulatable format. Matio library ( is required.
3. The Gnuradio flowgraph is also provided with the enhanced version of gr-adsb, in which you are supposed to replace the original one ( And, you can specify an output file path in the property panel of the ADS-B decoder submodule.
4. Related publication: Zero-Bias Deep Learning for Accurate Identification of Internet of Things (IoT) Devices, IEEE IoTJ (accepted for publication on 21 August 2020), DOI: 10.1109/JIOT.2020.3018677