Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Radar radiation source signal classification and identification method adopting ICGAN and ResNet networks

A technology of signal classification and identification method, applied in the field of digital communication, which can solve the problems of outdated identification requirements, inability to achieve higher efficiency and accuracy, etc., and achieve the effect of low loss rate, superior classification effect, and expanded quantity

Pending Publication Date: 2021-06-15
HANGZHOU DIANZI UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional signal analysis method is mainly realized through the analysis of conventional parameters such as pulse width and carrier frequency, and then matching the corresponding template. In today's situation where radar technology continues to develop and the electromagnetic environment is increasingly developing, it has been unable to achieve higher efficiency. and accuracy, thus falling far behind the needs of identification

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Radar radiation source signal classification and identification method adopting ICGAN and ResNet networks
  • Radar radiation source signal classification and identification method adopting ICGAN and ResNet networks
  • Radar radiation source signal classification and identification method adopting ICGAN and ResNet networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0054] In order to improve the accuracy of generative adversarial network sample generation, an improved conditional generative adversarial network (ICGAN) is proposed here. Based on the traditional Generative Adversarial Network (GAN), ICGAN modifies the input of the discriminant network; the input of the discriminant network is not only real samples and real labels, but also wrong samples and wrong labels as input to participate in iterative training.

[0055] The purpose of the present invention is to address the deficiencies of the existing radar radiation source identification technology. In the case of insufficient samples, accurately extract the signal characteristics of different types of radar radiation sources and use ICGAN to expand the samples, and then use the ResNet network to accurately realize the radar radiation. Discrimination of source signal type.

[0056] (1) Steps to obtain the radar radiation source dataset

[0057] Step 1.1, separate the aliased signal...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a radar radiation source signal classification and identification method adopting an ICGAN and ResNet network, and the method comprises the following steps: 1, receiving aliasing signals through a receiver, separating the aliasing signals, and generating six common radar radiation source signal data sets, and 2, carrying out a signal preprocessing method; 3, constructing an ICGAN, 4, constructing a deep residual network (ResNet), and 5, inputting the test set sample into the ResNet, and outputting a recognition result of radar radiation source signal classification. The method aims to extract different types of radar radiation source signal features under the condition that the number of samples is insufficient, the number of the samples is expanded by utilizing ICGAN, and then the types of the radar radiation source signals are accurately distinguished by utilizing ResNet; the method not only can solve the problem that the number of samples is insufficient, but also can improve the recognition rate of different types of radar radiation source signals.

Description

technical field [0001] The invention belongs to the technical field of digital communication, and in particular relates to a method for classifying and identifying radar radiation source signals using ICGAN and ResNet networks. Background technique [0002] As an important part of electronic technology reconnaissance, the identification of radar emitters has always been a hot research topic in the field of communication countermeasures. Its main process is: measure the radiation source signal received by the receiver, analyze and process it, and identify the individual radar radiation source according to the existing prior information. The traditional signal analysis method is mainly realized through the analysis of conventional parameters such as pulse width and carrier frequency, and then matching the corresponding template. Under the situation of continuous development of radar technology and the development of electromagnetic environment, it has been unable to achieve hi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G06T7/45
CPCG06N3/084G06N3/088G06T7/45G06N3/045G06F2218/08G06F2218/12G06F18/214G06F18/241
Inventor 姜斌程子巍包建荣刘超唐向宏
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com