A multi-radar and communication signal classification method based on clustering analysis

A communication signal and cluster analysis technology, applied in the field of communication, can solve problems such as no solution

Active Publication Date: 2018-12-25
HOHAI UNIV
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However, the prior art does not have a good solution

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  • A multi-radar and communication signal classification method based on clustering analysis
  • A multi-radar and communication signal classification method based on clustering analysis
  • A multi-radar and communication signal classification method based on clustering analysis

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[0087] The recognition performance of the multi-signal classification algorithm is verified by MATLAB simulation. First, short-time Fourier transform is used to distinguish single-frequency signals from BPSK, QPSK, and 16QAM. During the simulation process, the single-frequency signal sampling frequency is set to 20MHz, the time width is 100us, the frequency is 100KHz, and the signal-to-noise ratio is 30dB. The symbol rate of the other three signals is set to 1MHz, the sampling rate is set to 200MHz, the carrier frequency is set to 10MHz, and the signal-to-noise ratio is 30dB. There are 200 training samples and 200 test samples each. After short-time Fourier transform of the four signals, the maximum frequency of each time window segment is obtained, and the mean square error of the maximum frequency is obtained. The mean square error graph of the four signals is shown in image 3 As shown, the classification threshold can be set to 0.1. In the test phase, this threshold is...

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Abstract

The invention discloses a method for classifying radar and communication signals based on clustering analysis, which comprises the following steps: extracting the information of the maximum frequencyof each time window section, and calculating the mean square error of the information; classification threshold value is set, and the threshold value is applied to the classification of test samples to distinguish the single frequency signal SF and [BPSK, QPSK, 16QAM] signals; the phase mean square deviation is used as one signal identification feature and the instantaneous amplitude mean square deviation is used as another signal feature. The training samples and test samples of BPSK, QPSK and 16QAM signals are generated respectively, and the BPSK, QPSK and 16QAM signals are effectively classified by clustering analysis algorithm. The invention adopts the multi-level classification and identification technology, combines the short-time Fourier transform and the clustering analysis algorithm, and realizes the layer-by-layer separation of the radar and the communication signals of different modulation types.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a method for classifying various radar and communication signals based on cluster analysis. Background technique [0002] With the development of communication technology, the wireless communication environment is becoming more and more complex. Radar and communication signals adopt a variety of modulation methods, and the modulation parameters are also different. The modulation identification and parameter extraction of radar and communication signals provide important content for communication intelligence and are the premise of jamming and intercepting enemy communication. How to effectively identify and monitor these signals is a very important research topic in both military and civilian fields. However, there is no good solution in the prior art. Contents of the invention [0003] In view of the above-mentioned defects of the prior art, the technical problem to be...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L27/00G06K9/62
CPCH04L27/0012G06F18/23213G06F18/24
Inventor 王峰杨晨璐
Owner HOHAI UNIV
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