Method for estimating complex micro-motion space cone target parameters by using deep learning convolutional neural network

A convolutional neural network and deep learning technology, applied in the field of using convolutional neural network to estimate the geometric parameters and fretting parameters of complex micro-movement space pyramid targets, which can solve the problems of short flight time, recognition and interception of Dato's , to achieve the effect of high precision, rapid testing process and quick results

Pending Publication Date: 2020-08-28
NANJING UNIV OF SCI & TECH
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Problems solved by technology

Among them, the flight time of the initial stage and the reentry stage is rel...

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  • Method for estimating complex micro-motion space cone target parameters by using deep learning convolutional neural network
  • Method for estimating complex micro-motion space cone target parameters by using deep learning convolutional neural network
  • Method for estimating complex micro-motion space cone target parameters by using deep learning convolutional neural network

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Embodiment

[0083] Aiming at the problem that the micro-Doppler frequency of the equivalent scattering center changes complicatedly when the blunt flat-bottomed cone model nutates, it is difficult to extract the micro-Doppler frequency curve, and the mathematical modeling is difficult. The previous estimation method is difficult to effectively estimate the target parameters. . The so-called nutation refers to the precession of the target accompanied by a certain swing, so the change of the nutation angle is to increase the two factors of swing amplitude and swing frequency on the basis of the precession angle, the expression is as follows:

[0084] θ'=A·sin(ω't)+θ

[0085] Among them, A is the swing amplitude, ω' is the swing frequency, and θ is the precession angle. It can be seen from the above formula that when A=0, ω'=0, nutation becomes precession, so it can be considered that precession is a special form of nutation, and nutation is a more generalized form of cone target motion. a...

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Abstract

The invention discloses a method for estimating complex micro-motion space cone target parameters by using a deep learning convolutional neural network. The method comprises the following steps of: firstly, a ballistic missile target geometric model is established; then, a single-frequency pulse is emitted to a target; echoes of a target are received, time-frequency analysis is performed on the target echo to obtain a time-frequency distribution diagram of the target; the time-frequency graph is used as the input of the CNN, so that the network learns the features of the time-frequency graph;the cone target height, and estimated values of a bottom surface radius and a precession angle are finally obtained; the method for estimating the space cone target comprises the following steps of: estimating a micro Doppler frequency curve of the target from a time-frequency diagram; the method has poor stability, the estimated micro Doppler frequency has great influence on a parameter estimation result; according to the method provided by the invention, the features are directly extracted from the time-frequency diagram, the estimation stability and precision are improved, the previous method can only estimate the precession target, and the method provided by the invention not only can estimate the precession space cone target, but also can estimate the parameters of the nutation spacecone target.

Description

technical field [0001] The invention belongs to the technical field of signal processing, in particular to a method for estimating geometric parameters and fretting parameters of a complex fretting space cone target by using a convolutional neural network. Background technique [0002] When the ballistic missile is flying at high speed in the air, the spin motion maintains the stability of its attitude, and the lateral disturbance will convert the spin motion into a precession form, where the spin refers to the ballistic missile's rotational motion around its own symmetry axis, Motion refers to the rotation of the ballistic missile around the cone axis while spinning. [0003] Space target recognition is a crucial link in the ballistic missile defense system. The mid-stage flight is the longest in the flight process of a ballistic missile, and the space environment is relatively simple. At this time, the target is shown as a small rotation around the center of mass while th...

Claims

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Application Information

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IPC IPC(8): G06N3/08G06N3/04G06T17/00G01S13/50
CPCG06N3/084G06T17/00G01S13/50G06N3/045
Inventor 陈如山丁大志樊振宏何姿李猛猛叶晓东张杰张晓杰
Owner NANJING UNIV OF SCI & TECH
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