Multi-fractal feature aircraft target classification method based on principal component analysis

A technique of principal component analysis and aircraft targeting, applied in climate sustainability, instrumentation, ICT adaptation, etc., can solve problems such as low classification recognition rate

Active Publication Date: 2019-01-08
GANNAN NORMAL UNIV
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Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention proposes a multi-fractal feature aircraft target classification method based on principal component analysis to solve the problem of low classification and recognition rate of low-resolution radar due to limitations of factors such as system and noise

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  • Multi-fractal feature aircraft target classification method based on principal component analysis
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Embodiment Construction

[0064] refer to figure 1 , the implementation of the present invention includes two stages of training and testing.

[0065] 1. Training stage

[0066] Step 1, get the time domain training sample set

[0067] Select m groups of aircraft echo signals as the original radar echo data of the test data from the aircraft radar echo signals, X={x 1 ,x 2 ,...,x i ,...x m}, where x i ' represents the i-th time-domain test sample, and m represents the total number of test samples.

[0068] Step 2, calculate the third-order Renyi information entropy value of the aircraft target echo signal

[0069] The third-order Renyi information entropy formula of the aircraft target echo is as follows:

[0070] v=-1 / 2∑ k log(|FRFT P (K)| 3 )

[0071] FRFT(k) represents the aircraft target signal after Fractional Fourier Transform, p is the order of Fractional Fourier Transform, P=[p 1 ,p 2 ,...,p k ], where P belongs to [0,2], the step size is 0.02, k=100, v represents the third-order ...

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Abstract

The invention discloses a multi-fractal feature aircraft target classification method based on principal component analysis, which belongs to the technical field of radars, relates to an aircraft target classification method based on multi-fractal features, and mainly solves the problem of low recognition rate of aircraft target classification caused by the factors such as low pulse repetition frequency and short irradiation time of a low-resolution radar. The method comprises the implementation processes as follows: preprocessing original radar echo data; performing fractional Fourier transform on the processed radar echo data; analyzing the multi-fractal features of the radar echo data in an optimal fractional Fourier domain and extracting the multi-fractal features to form feature vectors; performing principal component analysis on the feature vectors after normalization, and performing classification and identification on the aircraft targets by using the extracted effective features; training a classifier by training sample feature vectors; and inputting the testing sample feature vectors into the classifier for classification. The multi-fractal feature aircraft target classification method based on principal component analysis still has good classification effect under the condition of low pulse repetition frequency and short irradiation time, and can be used for classification identification of aircraft targets.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to a low-resolution radar aircraft target classification method, which can be used for classifying and identifying different types of aircraft targets. Background technique [0002] Most of the active air defense warning radars are conventional low-resolution system radars, which are mainly used for target detection and tracking. In modern warfare, various types of aircraft such as jet aircraft, propeller aircraft, and helicopters undertake different tasks and cooperate with each other to complete combat objectives. Therefore, it is of great significance to realize the classification and identification of low-resolution radar aircraft targets. [0003] Due to the limitations of the low-resolution radar system and the influence of background noise and other factors, the classification and recognition rate of conventional low-resolution radar aircraft targets is low. Studies have shown t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/411G01S7/418Y02A90/10
Inventor 李秋生张华霞谢晓春
Owner GANNAN NORMAL UNIV
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