Adaptive radiation source modulation identification method based on time-frequency analysis

A time-frequency analysis and modulation recognition technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of high signal-to-noise ratio feature redundancy and low signal-to-noise ratio feature missing.

Active Publication Date: 2017-10-27
HARBIN ENG UNIV
View PDF3 Cites 32 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an adaptive radiation source modulation recognition method based on time-fre...

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
  • Adaptive radiation source modulation identification method based on time-frequency analysis
  • Adaptive radiation source modulation identification method based on time-frequency analysis
  • Adaptive radiation source modulation identification method based on time-frequency analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] 1. The experimental parameters are set as follows: Simulate and analyze the radar emitter signals of four modulation modes: LFM, BPSK, COSTAS, and FRANK. The carrier frequency is 20MHz, the sampling frequency is 100MHz, the pulse width is 10us, and BPSK is 7-bit Barker code. . For each signal to be classified, the simulation test is carried out every 2dB when the signal-to-noise ratio is between -2 and 20dB. Each signal generates 200 samples under the current signal-to-noise ratio, and each signal randomly selects 140 samples. SVM training is carried out, and the remaining 60 samples are used for testing the recognition rate of the SVM classifier. Test results such as Figures 3 to 5 shown.

[0062] in image 3 Indicates the determination of the estimated value of the signal-to-noise ratio of the radiation source. According to the estimation of the AWGN channel in step 3, taking the BPSK modulation signal as an example, the range of the signal-to-noise ratio to be es...

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 provides an adaptive radiation source modulation identification method based on time-frequency analysis. The method comprises the steps of I, carrying out time-frequency analysis on a received radiation source signal by use of time frequency distribution, converting the radiation signal from a time-domain signal to a time-frequency two-dimensional image; II, reducing computation complexity and characteristic dimension by use of an image processing technology, and improving the proportion of signal characteristic information in the image through normalization, binaryzation, image thinning and image preprocessing operations; III, carrying out image shape characteristic extraction on the preprocessed image in combination with a second-order and four-order moment estimation method by use of an adaptive principal component analysis algorithm; and IV, identifying a modulation mode of the radiation source signal by use of an LIBSVM (Library for Support Vector Machine) classifier. According to the adaptive radiation source modulation identification method based on time-frequency analysis, the characteristic missing of a low signal to noise ratio signal can be effectively avoided, and characteristic redundancy of a high low signal to noise ratio can be also avoided, and the modulation identification rate is not affected at the same time.

Description

technical field [0001] The invention relates to a method for identifying intrapulse modulation of radiation source signals. Background technique [0002] Intra-pulse modulation identification of radiation source signal is one of the important characteristics of radiation source, and it is an important parameter in non-cooperative communication methods such as receiving, sorting and positioning of radiation source. The signal density of the electromagnetic threat environment is as high as 1.2 million pulses per second. The radar operating frequency coverage has reached 0.1-20GHz, and is expanding to 0.05-140GHz. The radar signal waveform changes simultaneously in multiple domains such as time and frequency. The modulation identification of radiation source signals faces problems such as complex electromagnetic environment, diverse modulation styles, and low signal-to-noise ratio. [0003] In recent years, a large number of research results on radar emitter signal recognition...

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): G06K9/62G06K9/00
CPCG06F2218/08G06F2218/12G06F18/2135G06F18/2411
Inventor 高敬鹏孔维宇郜丽鹏吴冰蒋伊琳赵忠凯孙恒梁旭华
Owner HARBIN ENG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap