Between-class separability enhanced subspace true and false target characteristic extraction method

An extraction method and a technology of target features, which are applied in the field of class separation enhanced subspace true and false target feature extraction, can solve the problems of regular subspace method recognition performance degradation, etc., to achieve improved target recognition performance, high recognition rate, and increased separation degree of effect

Active Publication Date: 2018-11-16
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0003] However, the conventional canonical subspace weights the target data equally when establishing the transformation matrix. When the distribution areas of the target data are close to each other, the

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  • Between-class separability enhanced subspace true and false target characteristic extraction method
  • Between-class separability enhanced subspace true and false target characteristic extraction method
  • Between-class separability enhanced subspace true and false target characteristic extraction method

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[0034] The actual application effect of the present invention is described below in conjunction with simulation data:

[0035] Four point targets are designed: true target, fragment, light bait, and heavy bait. The bandwidth of the radar emission pulse is 1000MHZ (the distance resolution is 0.15m, the radar radial sampling interval is 0.075m), the target is set as a uniform scattering point target, the scattering points of the real target are 7, and the scattering points of the other three targets are all 11 . In the one-dimensional range images with target attitude angles ranging from 0° to 80° at intervals of 1°, take the one-dimensional distances with target attitude angles of 0°, 2°, 4°, 6°,...,80° The one-dimensional range images of the other attitude angles are used as test data, and there are 40 test samples for each type of target.

[0036] For the four kinds of targets (true target, debris, light decoy and heavy decoy), within the range of attitude angle 0°~80°, usi...

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Abstract

The invention belongs to the technical field of radar target identification and specifically relates to a between-class separability enhanced subspace true and false target characteristic extraction method. According to the invention, the between-class separability level is utilized as an enhancement factor for increasing the effect of a data sample with large between-class separability in a subspace establishment process, so that the separability between different classes is increased further and the target identification performance is improved. Even superposition exists in target areas, a high identification rate can also be achieved. Simulation tests are performed on one-dimensional distance image data of four classes of simulation targets and the test results prove the effectiveness of the method.

Description

technical field [0001] The invention belongs to the technical field of radar target recognition, in particular to a method for extracting features of real and false targets in a class separation enhanced subspace. Background technique [0002] In radar target recognition, regularized subspace method is an effective feature extraction method. The canonical subspace method can increase the difference between heterogeneous target features and reduce the difference between similar target features. Therefore, the canonical subspace method has good classification performance. [0003] However, the conventional canonical subspace weights the target data equally when establishing the transformation matrix. When the distribution areas of the target data are close to each other, the recognition performance of the canonical subspace method will decrease. Therefore, there is room for further improvement in the recognition performance of existing conventional regularized subspace method...

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Application Information

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IPC IPC(8): G01S13/02G01S7/41
CPCG01S7/41G01S13/02
Inventor 周代英张瑛冯健
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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