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Convolutional neural network based SAR moving target indication method

A convolutional neural network and moving target detection technology, applied in the field of radar, can solve problems such as difficult to meet practical applications, high requirements for the number of data range gates, limited application of MTI methods, etc., to avoid class imbalance problems, the number of The effect of requiring less and reducing the degree of overfitting

Inactive Publication Date: 2019-05-03
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

However, these methods have shortcomings such as high requirements on the number of range gates available for the auxiliary data of the target to be detected, or the detection can only be realized when the SAR moving target signal-clutter power is relatively high, so the application of the existing MTI method is limited , it is difficult to meet the needs of practical applications

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  • Convolutional neural network based SAR moving target indication method
  • Convolutional neural network based SAR moving target indication method
  • Convolutional neural network based SAR moving target indication method

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Embodiment Construction

[0022] In order to describe content of the present invention conveniently, at first do following term definition:

[0023] Definition 1. Space-time observation matrix

[0024] The space-time observation matrix X is a two-dimensional matrix, which stores the result of SAR echo signal distance compression. Each row of the two-dimensional matrix represents each pulse, and each column represents each antenna channel. The mth row of the two-dimensional matrix The mathematical expression of n column elements is

[0025]

[0026] The first term in formula (1) represents the echo of the SAR moving target signal, and the second term χ m,n Represents clutter and noise interference, m=1,...,M, n=1,...,N, M is the number of transmitted pulses in a coherent processing interval, N is the number of antenna channels, m and n are respectively index of the pulse and antenna, α is the amplitude of the moving target, is a random phase, l n =L n / λ,L n is the distance between the nth ant...

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Abstract

The invention discloses a convolutional neural network based SAR moving target indication method, and is applied to the field of SAR moving target indication. For defects in the prior art of high requirements for the number of available to-be-detected target auxiliary data range gates, the method calculates target speed by constructing a convolutional neural network and training the neural networkaccording to the total Doppler frequency obtained through the detection of the neural network and angles of target relative synthetic apertures, so that SAR moving target indication can be realized;and the method can realize detection under the circumstance of a small number of the available to-be-detected target auxiliary data range gates.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a moving target detection technology of a synthetic aperture radar (Synthetic Aperture Radar, abbreviated as SAR). Background technique [0002] Moving Target Indication (MTI) technology is a key technology of synthetic aperture radar. The moving target detection technology can detect the moving target within the irradiation range of the beam, and estimate the moving target parameters such as its moving speed. [0003] Traditional MTI methods mainly include space time adaptive processing (Space time adaptive processing, abbreviated as STAP) (reference 1: L.E.Brennan, L.S.Reed. Theory of adaptive radar [J]. IEEETransactions on Aerospace and Electronic Systems, 1973, 9( 2):237-252), and various improved algorithms of STAP (reference 2: H.Wang, L.Cai.On adaptive spatial-temporal processing for airborne surveillance radar systems[J].IEEE Transactions on aerospace and elect...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/58G01S7/02G06N3/04
Inventor 刘喆许晓晴
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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