Large scale radio frequency signal information processing and analysis system using bin-wise processing

A method for classifying telecommunication signals, comprising:

• receiving signal information;
• processing the signal information through an image processing algorithm in the time domain to produce a first compact dataset;
• transforming the signal information into the frequency domain;
• processing the signal information through the image processing algorithm in the frequency domain to produce a second compact dataset;
• and
• using the first and second compact datasets to train machine learning algorithms to detect, identify, and classify telecommunication signals, wherein using the first and second datasets to train the machine learning algorithms to detect, identify, and classify telecommunication signals comprises using the first and second datasets to train the machine learning algorithms to:
• determine distribution of in-phase and quadrature-phase signals,
• compare the distribution of the in-phase and quadrature-phase signals over a frequency band of interest against noise distribution, and
• apply thresholds to isolate signals.

A non-transitory computer-readable medium that stores a set of instructions which when executed perform a method executed by the set of instructions comprising:

• receiving signal information;
• processing the signal information through an image processing algorithm in the time domain to produce a first compact dataset;
• transforming the signal information into the frequency domain;
• processing the signal information through the image processing algorithm in the frequency domain to produce a second compact dataset;
• and
• using the first and second compact datasets to train machine learning algorithms to detect, identify, and classify telecommunication signals, wherein using the first and second datasets to train the machine learning algorithms to detect, identify, and classify telecommunication signals comprises sing the first and second datasets to train the machine learning algorithms to:
• determine distribution of in-phase and quadrature-phase signals,
• compare the distribution of the in-phase and quadrature-phase signals over a frequency band of interest against noise distribution, and
• apply thresholds to isolate signals.