SVDD radar target one-dimensional distance image identification method based on density weight and hybrid kernel function

A hybrid kernel function and radar target technology, applied in the field of one-dimensional range image recognition of SVDD radar targets, can solve the problems of weak generalization performance, large amount of calculation, and performance degradation of the recognition algorithm, so as to avoid complex exponential operations and generalization. Strong ability to improve the effect of recognition performance

Active Publication Date: 2018-01-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

The traditional SVDD algorithm usually uses the radial basis kernel function as the kernel function, but the radial basis kernel function has the disadvant

Method used

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  • SVDD radar target one-dimensional distance image identification method based on density weight and hybrid kernel function
  • SVDD radar target one-dimensional distance image identification method based on density weight and hybrid kernel function
  • SVDD radar target one-dimensional distance image identification method based on density weight and hybrid kernel function

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Embodiment

[0035] In order to verify the effectiveness of the present invention, the following simulation experiments are performed.

[0036] The one-dimensional range profile data of five simulated aircraft targets were identified, including five types of aircrafts: AH64, AN26, B52, B1B, and F15. The radar bandwidth is 400MHZ, and the operating frequency is 6GHz. In the one-dimensional range image of every 0.1° within the range of target attitude angle of 0°~30°, take the 0°, 0.2°, 0.4°,..., 30° of the AH64 one-dimensional range image as the training sample data; AN26, B52, B1B, F15 one-dimensional range images of 0°~15° range of one-dimensional range images are respectively combined with the remaining sample data in the range of 0°~30° in AH64 to form test data.

[0037] For the recognition of 5 kinds of targets, the existing SVDD and the one-dimensional range profile recognition algorithm of SVDD radar target based on density weight and hybrid kernel function proposed by the present inven...

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Abstract

The invention discloses an SVDD radar target one-dimensional distance image identification method based on density weight and a hybrid kernel function and belongs to the radar target identification field. The K-type kernel function has strong generalization capability, extraction of global characteristics of training data is facilitated, complex index operation of a radial basic kernel function isavoided, and properties of small calculation complexity of a polynomial kernel function and high approximation precision of the radial basic kernel function are realized. The radial basic kernel function has quite good local characteristics, the K-type kernel function and the radial basic kernel function are combined to replace a kernel function of a traditional SVDD algorithm, moreover, a localdensity algorithm based on interception distance is employed to calculate local density between a support vector and training sample data in the high-dimensional kernel characteristic space, accordingto density distribution, the shape of a super-closed ball is adjusted, and identification performance of radar one-dimensional distance image single type targets is effectively improved.

Description

Technical field [0001] The invention is suitable for the field of radar target recognition, and specifically relates to a one-dimensional range profile recognition of SVDD radar target based on density weight and hybrid kernel function. Background technique [0002] The Radar High Resolution Range Profile (HRRP) is the projected vector sum of the scattered point echoes of the target to be identified along the line of sight of the radar, which reflects the distribution of the scattered points of the target on the line of sight of the radar. Compared with the radar cross-section (RCS) of the target obtained by the low-resolution radar, it can obtain more information about the structure and shape of the target; compared with the synthetic aperture radar (Synthetic ApertureRadar, SAR) image Compared with the Inverse Synthetic Aperture Radar (ISAR) image, it has the characteristics of easy acquisition and small storage capacity, so it has been widely used in the field of Radar Automat...

Claims

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Application Information

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IPC IPC(8): G01S7/41
Inventor 周代英但瑞李文辉
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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