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Electromagnetic target intelligent clustering method based on bispectral characteristics

A clustering method and spectral feature technology, which is applied in the field of intelligent clustering of electromagnetic targets, can solve the problems of affecting the target clustering effect and the target discrimination degree is not obvious, so as to improve the clustering accuracy, improve the processing capacity, and improve the processing performance effect

Active Publication Date: 2020-09-25
SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a method for clustering space electromagnetic target signals by using the signal bispectrum (third-order cumulant of signal) feature to solve the current electromagnetic target signal clustering problem. Method In the environment where the radiation parameters of multiple targets are similar, the target discrimination is not obvious, which affects the effect of target clustering, so as to realize the high-precision clustering of target signals under the similar radiation parameters of multiple targets and improve the clustering performance of radiation sources

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  • Electromagnetic target intelligent clustering method based on bispectral characteristics
  • Electromagnetic target intelligent clustering method based on bispectral characteristics
  • Electromagnetic target intelligent clustering method based on bispectral characteristics

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[0030] The present invention will be further described below in conjunction with the accompanying drawings.

[0031] Such as figure 1 As shown, the present invention provides a method for intelligent clustering of electromagnetic targets based on bispectral features, and the specific process is as follows:

[0032] 1. Data preprocessing: Perform data cleaning, DC removal, and normalization preprocessing on the received intermediate frequency data to be clustered.

[0033] Data cleaning: First, data cleaning is performed on the intermediate frequency data. By setting an appropriate signal-to-noise ratio threshold, the pulse samples with low signal-to-noise ratio and incomplete collection are eliminated, and the cleaned data sample set x is obtained. step1 (n).

[0034] Data to DC: For the cleaned N-point intermediate frequency data x step1 (n)=[x 1 ,x 2 ,...x N ],n=1,2,...N to be summed to obtain the sequence and value Then divide this sum by the total number of data to...

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Abstract

The invention relates to the technical field of electromagnetic target intelligent clustering, and discloses an electromagnetic target intelligent clustering method based on bispectral characteristics. The method comprises the steps: performing the preprocessing of pulse-by-pulse DC removal, noise reduction and energy normalization by utilizing received radiation source intermediate frequency data, and then extracting bispectrum (three-order cumulant) characteristics of pre-monopulse data one by one; performing clustering calculation by utilizing a Kmeans method by calculating the Euclidean distance of each monopulse bispectrum sequence, and completing the intelligent clustering of targets is completed. According to the invention, the characteristic that the bispectral characteristic of the pulse signal is not easily polluted by Gaussian white noise is utilized; the method directly starts from the collected intermediate frequency data, does not need to extract the intra-pulse and inter-pulse parameters of the target, is not sensitive to the similarity of the radiation source parameters, and can improve the signal clustering capability of the radiation source with similar parametersin a complex environment.

Description

technical field [0001] The invention relates to the technical field of intelligent clustering of electromagnetic targets, in particular to an intelligent clustering method of electromagnetic targets based on bispectral features. Background technique [0002] The traditional electromagnetic target clustering technology is to use the pulse description word (including signal amplitude, frequency, pulse width, azimuth, pulse repetition period) obtained by measuring the target and the modulation information in the pulse of the signal (frequency modulation type and modulation parameters, Phase modulation type and modulation parameters, etc.) for feature extraction and law mining, by setting appropriate discrimination criteria, the pulse groups with similar characteristic laws are classified into the same category, and the pulse groups with different characteristic laws are classified into different categories, so as to complete the comparison. Clustering of objects. In the tradit...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23213
Inventor 马巍王杰李晓李锐洋旷生玉徐晶
Owner SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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