RF Fingerprinting of DSP Implementations using Machine Learning: An Over-the-Air Case Study
The study investigated using machine learning to perform RF fingerprinting based on Digital Signal Processing (DSP) implementations of RTTY communication software. By comparing signals generated by different DSP packages, researchers found that differences in numerical quantization and filtering create distinguishable signal characteristics. The results indicate that combining raw IQ data with power spectrum analysis provides the best accuracy for emitter identification, especially under high SNR conditions.