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Radiation source individual characteristic enhancement method based on time-varying filtering theory

A technology of time-varying filtering and feature enhancement, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of identification failure and low identification accuracy of radiation source individuals, and achieve the effect of enhancing the characteristics of radiation source individuals

Active Publication Date: 2019-08-20
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of low identification accuracy of the existing radiation source individual and the identification failure caused by the change of the main signal parameters, and propose a radiation source individual feature enhancement method based on time-varying filtering theory

Method used

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  • Radiation source individual characteristic enhancement method based on time-varying filtering theory
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  • Radiation source individual characteristic enhancement method based on time-varying filtering theory

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specific Embodiment approach 1

[0041] Specific implementation mode one: combine figure 1 Describe this embodiment. In this embodiment, a method for enhancing individual characteristics of a radiation source based on time-varying filtering theory has a specific process as follows:

[0042] Step 1. The receiver receives the radiation source signal. The radiation source signal is a multi-component signal s(t), which includes multiple signal components and can be divided into three parts. First, the signal of the target radiation source itself and the interference signals of other radiation sources are both Belonging to the main signal, the energy of this part is relatively high, and the component can be directly extracted from the time-frequency distribution; second, the individual radiation source adds the modulation signal component, which is the part to be enhanced and feature extracted by this algorithm, and the energy of this part Low, it cannot be directly extracted from the time-frequency distribution; ...

specific Embodiment approach 2

[0074] Specific embodiment 2: The difference between this embodiment and specific embodiment 1 is that in the first step, the time-frequency distribution calculation is performed on the multi-component signal, and the time-frequency information is extracted to obtain the time-frequency of each signal component in the main signal component information; the specific process is:

[0075] The instantaneous frequency estimation algorithm based on the adaptive fractional spectrogram method calculates the time-frequency distribution of the multi-component signal, and extracts the time-frequency information to obtain the time-frequency information of each signal component in the main signal component.

[0076] Time-frequency distribution calculation and time-frequency information extraction can refer to literature (Khan N A, BoashashB.Instantaneous Frequency Estimation of Multicomponent Nonstationary Signals Using Multiview Time-Frequency Distributions Based on the Adaptive Fractional ...

specific Embodiment approach 3

[0078] Specific embodiment 3: The difference between this embodiment and specific embodiment 1 or 2 is that the radiation source signal in step 2 or 2 is based on the time-varying short-time fractional Fourier order of the i-th signal component time-frequency information in the main signal. Transformation Kernel During Leaf Transformation The expression is:

[0079]

[0080] Among them, α i (τ) = πp i (τ) / 2 is the rotation angle of FrFT; j is the imaginary unit, j 2 =-1; k is an integer; δ(·) is an impact function; p i (τ) is the order time-varying function of the i-th signal component in the main signal component.

[0081] Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention discloses a radiation source individual characteristic enhancement method based on a time-varying filtering theory, and relates to a radiation source individual characteristic enhancement method. The objective of the invention is to solve the problems of low individual identification accuracy of an existing radiation source and identification failure caused by change of main signal parameters. The method comprises the following steps of: 1, performing time-frequency distribution calculation on a multi-component signal, and extracting time-frequency information to obtain time-frequency information of each signal component in a main signal component; 2, recovering and separating signal components in the main signal components one by one based on a time-varying filtering algorithm of order time-varying short-time fractional Fourier transform to obtain an estimation result of the sum of the main signal components; 3, subtracting an estimation result of the sum of the main signal components from the radiation source signal to obtain a residual component of the multi-component signal; 4, performing feature extraction on the residual component, and constructing a feature vector; and 5, inputting the constructed feature vectors into a classifier, and outputting a classification and recognition result. The method is applied to the field of radiation source individual characteristic enhancement.

Description

technical field [0001] The invention relates to a method for enhancing individual characteristics of radiation sources. Background technique [0002] Radiation source individual identification, also known as "radiation source fingerprint identification" or "specific radiation source identification", mainly uses passively received radiation source signals to analyze its subtle characteristic parameters, and uses subtle individual feature extraction to distinguish the different radiation sources of the same type. individual. Due to the difference in the physical components of the radiation source, each radiation source waveform has unique characteristics, which are called fingerprint features, and the key technology of individual radiation source identification lies in the selection and extraction of fingerprint features. Individual identification of radiation sources has many applications in both military and civilian applications. Military applications are mainly for indiv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/2413G06F18/24
Inventor 吴龙文赵雅琴王昭何胜阳任广辉
Owner HARBIN INST OF TECH
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