Signal rapid identification method based on frequency spectrum template

Abstract

The invention discloses a signal rapid identification method based on a frequency spectrum template, and belongs to the field of frequency spectrum monitoring and signal interference troubleshooting. The method comprises the steps of carrying out learning training through a machine learning method based on a Gaussian process and a Bayesian decision according to the signal frequency spectrum contour information in a known signal library, and building a signal identification model based on the frequency spectrum template; and then according to the constructed signal identification model based on the frequency spectrum template, adopting an advanced parallel computing architecture, and carrying out rapid matching identification on unknown signals by using the signal rapid identification model based on the frequency spectrum template so as to realize rapid identification of the unknown signals. IQ data of the signal does not need to be extracted, the identification model can be established according to the frequency spectrum contour information of the signal, and rapid matching identification can be performed according to the frequency spectrum contour of the unknown signal; and in order to solve the problem that signals are complex and time-consuming to process, a high-efficiency parallel computing analysis architecture based on the signal identification model is established, and rapid generation of the model and rapid identification of unknown signals are achieved.

Description

technical field [0001] The invention belongs to the fields of frequency spectrum monitoring and signal interference investigation, and in particular relates to a method for quickly identifying signals based on a frequency spectrum template. Background technique [0002] With the development of electronic technology, various new types of information equipment continue to appear, and electromagnetic radiation sources radiate more and more electromagnetic signals, forming a complex electromagnetic environment with wide frequency bands, multiple types, and rapid changes. In this case, the demand for signal identification capabilities in complex electromagnetic environments is becoming more and more urgent. According to application requirements, real-time and rapid identification of signals needs to be realized. However, the existing technical means only have identification based on IQ signals. Ability, does not have the ability to quickly identify signals based on spectrum templ...

AI Technical Summary

Problems solved by technology

In this case, the demand for signal identification capabilities in complex electromagnetic environments is becoming more and more urgent. According to application requirements, real-time and rapid identification of signals needs to be realized. However, the existing technical means only have identification based on IQ signals. ability, does not have the ability to quickly identify signals based on spectrum template matching

[0003] Moreover, there are two problems in the current fast signal identification method: first, the principle of the existing signal identification method is based on the identification of the IQ signal, and a series of processing needs to be carried out in the process of obtaining the IQ signal, and this processing needs to consume a certain amount of time, resulting in Its identification speed is slow; second, there are many signals in a complex electromagnetic environment. If each signal is processed and identified, it will seriously affect the work efficiency and cannot meet the requirements of real-time monitoring

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