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Method for steadily classifying ground moving target based on super-resolution Doppler spectrum

A ground moving target and Doppler spectrum technology, which is applied to the classification of moving vehicle targets and the field of target classification, can solve problems such as difficult to accurately express micro-Doppler information, poor classification performance of ground moving targets, and insufficient resolution, etc., to achieve Good ground moving target classification performance, improved classification performance, and the effect of improved classification performance

Inactive Publication Date: 2012-10-10
XIDIAN UNIV
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  • Summary
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  • Application Information

AI Technical Summary

Problems solved by technology

Due to insufficient resolution, it is difficult for existing technologies to accurately express these micro-Doppler information
Due to the existing problems in the above-mentioned clutter and noise suppression and low resolution of the existing methods, the classification performance of the existing methods for ground moving objects under the condition of low signal-to-noise ratio is poor

Method used

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  • Method for steadily classifying ground moving target based on super-resolution Doppler spectrum
  • Method for steadily classifying ground moving target based on super-resolution Doppler spectrum
  • Method for steadily classifying ground moving target based on super-resolution Doppler spectrum

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] Step 1, divide the Doppler echo signal into training data set and test data set

[0032] In order to realize the classification of ground moving targets, it is necessary to divide the Doppler echo signal collected by the radar into a training data set and a test data set, in which the training data set is used to train the classifier, and the test data set is used for classification. The following steps 2 to 7 have the same processing method for the Doppler echo signals in the training data set and the test data set, so steps 2 to 7 are based on a certain Doppler echo signal s={s 1 ,s 2 ,...,s N} as an example, where s n is the value of the nth point of the Doppler echo signal s, n=1, 2,..., N, N is the pulse accumulation number, and other Doppler echo signals are processed in the same way.

[0033] Step 2, perform Fourier transform on a certain Doppler echo signal s according to formula (1):

[0034] f m = ...

Embodiment 2

[0081] Step 1 is the same as Step 1 in Example 1.

[0082] Step 2 is the same as Step 2 in Example 1.

[0083] Step 3 is the same as Step 3 in Example 1.

[0084] Step 4 is the same as Step 4 in Example 1.

[0085] Step 5 is the same as Step 5 in Example 1.

[0086] Step six, calculate the super-resolution Doppler spectrum after adaptive clutter and noise suppression

[0087] Using the Fourier base dictionary B and the estimated noise energy ε to reconstruct the signal y after suppressing the clutter, and using the orthogonal matching pursuit algorithm to solve the problem with the minimum l 1 The super-resolution Doppler spectrum a of the norm is specifically carried out as follows:

[0088] 6a) Set the Fourier basis dictionary B as the basis function of the orthogonal matching pursuit algorithm;

[0089] 6b) Set the signal y after suppressing the clutter as the approximation signal of the orthogonal matching pursuit algorithm;

[0090] 6c) Set the iteration error less ...

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Abstract

The invention discloses a method for steadily classifying a ground moving target based on super-resolution Doppler spectrum, and mainly solves the problem that the classification performance is low because the signal structure is influenced during clutter reduction, the resolution ratio is low under short residence time and the noise cannot be suppressed in the conventional similar method. The method comprises the following steps of: calculating a short-time echo signal Doppler spectrum, and estimating the noise energy in the signal by utilizing the short-time echo signal Doppler spectrum; estimating a clutter autocorrelation matrix by utilizing a target approach distance unit; establishing a Fourier-based dictionary matrix, and solving the l1 norm optimization problem to obtain a super-resolution Doppler spectrum of a target; extracting characteristics of the super-resolution Doppler spectrum of the target; and classifying the extracted characteristics by using a classifier. By the method, the resolution ratio of the Doppler spectrum of the target is improved, the signal structure can be kept during adaptive clutter reduction, and the noise in the signal is suppressed; and moreover, the classification performance is improved, the noise robustness is obtained, and the method can be used for classifying moving vehicle targets with maneuvering parts.

Description

technical field [0001] The invention belongs to the technical field of radar and relates to a target classification method, which can be used to classify moving vehicle targets with motor parts. Background technique [0002] In the field of radar target classification and recognition, due to the different division of labor between wheeled and tracked vehicles in the battlefield environment, it is of great significance to classify wheeled and tracked vehicles. Usually, the radar echo of a moving vehicle target contains a lot of ground clutter, and due to the Doppler effect, the target will appear at a position deviated from zero frequency in the Doppler domain. In this way, the separation of moving targets and stationary ground clutter can be achieved. At the same time, the Doppler spectrum of the target also provides the motion information of the target itself, which can be used to classify and identify the target. [0003] Since the micro-Doppler concept was introduced in...

Claims

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Application Information

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IPC IPC(8): G01S7/41
Inventor 刘宏伟李彦兵杜兰纠博王鹏辉杨晓超
Owner XIDIAN UNIV
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