rfYOLO: Phase as a Modality for Signal Detection
A phase transform that improves PHY-layer signal characterisation using YOLO networks. rfYOLO studies phase as an additional modality, since spectrogram-based detectors discard phase information.
On a mixed dataset, YOLO on STFT magnitude alone identified CPFSK, FSK, and GFSK at 90–96% and PSK2 at 83%, likely because their spectral shapes differ, but could not separate QAM orders (26–32%). The transform removes the deterministic phase term introduced by the STFT and weights the result by magnitude. Raw STFT phase proved ineffective as a network input, while the corrected phase performed better. The surrounding pipeline, yoLight, uses a fast energy detector to gate YOLO inference, subtracts YOLO’s detections from the stream, and passes the remainder to the Searchlight energy detector to produce boxed IQ and signal metadata.