Broadband signal parameter estimation method based on deep learning

Abstract

The invention discloses a broadband signal parameter estimation method based on deep learning, aims to achieve the detection and recognition of a broadband specific signal based on a YOLOv4 network and a gray-scale time-frequency graph, and carry out the calculation and updating of a detection result, and obtain an estimation parameter of each detected broadband signal. The problems that an existing method is low in detection and recognition precision, inaccurate in parameter estimation, few in applicable types and seriously depends on expert priori are solved. The method mainly comprises the following steps: (1) generating a broadband specific signal training set; (2) training a YOLOv4 network; (3) detecting and identifying the broadband signal gray scale time-frequency graph; (4) calculating parameters of each detected and identified broadband specific signal; (5) judging parameters of the broadband specific signal; and (6) updating broadband specific signal parameters. The method has the advantages of high broadband specific signal detection and identification precision, accurate parameter estimation, universality and the like, and can be used for analyzing broadband signals in radio detection and investigation.

Description

Technical field[0001]The present invention belongs to the field of communication technology, and more is a further involving one of a widely learned broadband signal parameter estimation method in the field of wireless communication technology. The estimated wideband signal parameters in the present invention can be applied to radio detection and reconnaissance, broadband spectrum management, and various types of communication signal analysis products.Background technique[0002]With the development of communication technology and the increase in the actual application demand, the bandwidth required for signal transmission is getting wider and wider, and the broadband receiver is gradually replacing the reception of the narrowband receiver. In electronic reconnaissance, the detection interception for the signal for large bandwidth is a premise of subsequent signal identification, primary parameter estimation, signal intercept quantity, signal splicing, and characteristic discriminatio...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to address the above-mentioned deficiencies in the prior art, and propose a method for estimating broadband signal parameters based on deep learning, aiming at solving the problem of traditional broadband signal parameter estimation Algorithms need to design algorithms for detection and identification and parameter estimation separately, are only suitable for certain types, have fixed processing procedures, and require a large amount of expert prior knowledge and domain knowledge

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