Signal analysis method and system based on model for acquiring and identifying noise panoramic distribution

A signal analysis method based on obtaining and recognizing a noise panorama distribution model, comprising the following steps:

• S1:
• in a rich condition measurement environment, performing repeated measurements on a reference sample and a test sample to respectively obtain a plurality of measurement results, wherein each measurement result comprises a signal and different noise profiles, and a rich condition is a natural measurement condition that is not aimed to maintain consistency of external conditions, does not involve noise suppression, and comprises real complex noise factors;
• S2:
• processing the measurement results of the reference sample and the test sample to respectively form training data of the reference sample and the test sample, wherein the training data comprises a noise panorama or a partial noise panorama constituted by a plurality of noise profiles, the noise panorama is a predicted data statistical distribution model of a noise obtained by noise modeling;
• S3:
• based on the training data of the reference sample and the test sample, training an artificial intelligence model, to enable the model to recognize the signal and the noise from the measurement results, and distinguish between the reference sample and the test sample;
• and
• S4:
• inputting a measurement result of a sample to be recognized to the trained artificial intelligence model, wherein the trained artificial intelligence model outputs an identification result indicating whether the sample to be recognized is the reference sample or the test sample.