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A Fuzzy Membership One-Dimensional Distance Profile Multi-feature Fusion Method

A technology of multi-feature fusion and fuzzy membership, applied in radio wave measurement systems, instruments, etc., can solve the problems of recognition performance degradation and achieve the effect of improving classification performance and target recognition performance

Active Publication Date: 2022-08-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the differences in physical dimensions of different features, the fusion feature vector formed by concatenated fusion must be normalized before recognition, and this normalization process will lead to a decrease in the performance of recognition

Method used

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  • A Fuzzy Membership One-Dimensional Distance Profile Multi-feature Fusion Method
  • A Fuzzy Membership One-Dimensional Distance Profile Multi-feature Fusion Method
  • A Fuzzy Membership One-Dimensional Distance Profile Multi-feature Fusion Method

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Embodiment Construction

[0028] In order to verify the effectiveness of the proposed method, the following simulation experiments are carried out.

[0029] Four types of point targets are designed: True Target, Fragment, Light Decoy, and Heavy Decoy. The bandwidth of the radar transmit pulse is 1000MHZ (range resolution is 0.15m, and the radar radial sampling interval is 0.075m). The target is set as a uniform scattering point target. The scattering point of the real target is 7, and the scattering points of the other three targets are all 11. . In the one-dimensional range image every 1° in the range of the target attitude angle of 0° to 70°, take the one-dimensional distance of the target attitude angle of 0°, 2°, 4°, 6°, ..., 70° The one-dimensional distance images of the remaining attitude angles are used as test data, and there are 35 test samples for each type of target.

[0030] For four kinds of targets (true target, debris, light decoy and heavy decoy), in the range of attitude angle 0°~70°...

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Abstract

The invention belongs to the technical field of radar target recognition, in particular to a fuzzy membership degree one-dimensional range image multi-feature fusion method. The method of the invention firstly converts the length, scattering, mode transformation and other features extracted from the one-dimensional distance image into features of equal size through the feature dimension expansion, and then uses the fuzzy membership degree to weight and fuse the multi-class features to form a The comprehensive feature can make full use of the classification performance of multiple features, thereby improving the target recognition performance, and at the same time solving the problem that the classification performance is affected by different physical dimensions in conventional feature fusion.

Description

technical field [0001] The invention belongs to the technical field of radar target recognition, in particular to a fuzzy membership degree one-dimensional range image multi-feature fusion method. Background technique [0002] In radar target recognition, multiple types of features such as length, scattering, and pattern can be extracted from the one-dimensional range image, and each type of feature reflects the difference of different targets in a certain aspect, such as the length feature reflects the difference in the size of the target, The scattering feature information contains the difference information of the target in terms of structure and shape, and the feature subspace projection feature reflects the difference of the target data distribution in the direction of maximum energy. Therefore, adopting a single feature can only distinguish multiple classes of objects that differ in one feature. In radar target recognition, especially in true and false target recognit...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 周代英沈晓峰冯健张瑛
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA