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Class aggregation subspace true and false target one-dimensional range profile feature extraction method

A technology of feature extraction and range profiling, applied in the field of radar, can solve the problems of the discriminative vector subspace method, such as the decline of the recognition, the overlapping of heterogeneous target data distribution, and the inability to identify.

Active Publication Date: 2017-10-20
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0003] However, when the data distribution of the same kind of target is very scattered, resulting in serious overlap in the distribution of heterogeneous target data, the discriminant vector subspace method will be significantly reduced in recognition, and it will not be able to identify
Therefore, there is room for further improvement in the recognition performance of the discriminant vector subspace method

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  • Class aggregation subspace true and false target one-dimensional range profile feature extraction method

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Embodiment Construction

[0016] The present invention will be described below in conjunction with specific embodiments.

[0017] 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 60° at intervals of 1°, take the one-dimensional distances with target attitude angles of 0°, 2°, 4°, 6°, ..., 60° The one-dimensional range images of the other attitude angles are used as test data, and there are 30 test samples for each type of target.

[0018] For four kinds of targets (true targets, fragments, light decoys and heavy decoys), in the range of attitude angle 0o ~ 60o, using the cluster-like s...

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Abstract

The invention belongs to the technical field of radars, and particularly relates to a class aggregation true and false target one-dimensional range profile feature extraction method. According to the method, same-class target features are more compact, different-class target features are hugely separated, defects of a conventional subspace discrimination method are overcome, even if serious overlap happens to different target data distribution, good recognition effects can still be acquired, and the radar true and false target classification performance is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a method for extracting features of a one-dimensional range image of clustered true and false targets. Background technique [0002] In radar target one-dimensional range profile recognition, the principal component analysis subspace is composed of the principal components of the data covariance matrix, which can well represent the main energy of the target data, but it is not optimal in terms of classification. The discriminant vector subspace method can reduce the difference between the same class and increase the difference between the different classes at the same time, and has a certain improvement in classification performance than the principal component subspace method. [0003] However, when the data distribution of the same kind of target is very scattered, resulting in the serious overlapping of the data distribution of heterogeneous targets, the discriminati...

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Application Information

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IPC IPC(8): G01S7/292G01S7/41
CPCG01S7/292G01S7/411
Inventor 周代英张瑛廖阔
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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