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ShuffleNet-based radar signal RD image interference identification method and system

A radar signal and image interference technology, applied in the field of radar signals, can solve the problems of poor recognition performance of radar signal interference, achieve excellent recognition ability, improve recognition accuracy, and suppress useless characteristic noise

Pending Publication Date: 2021-10-08
XIDIAN UNIV
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  • Claims
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Problems solved by technology

However, since the channel shuffling and channel information interaction methods in the ShuffleNet model are manually set, they have certain limitations, resulting in poor performance in radar signal interference recognition in complex environments.

Method used

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  • ShuffleNet-based radar signal RD image interference identification method and system
  • ShuffleNet-based radar signal RD image interference identification method and system
  • ShuffleNet-based radar signal RD image interference identification method and system

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Embodiment Construction

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0049] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.

[0050] It should also be understood that the terminology used ...

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Abstract

The invention discloses an improved ShuffleNet-based radar signal RD image interference identification method and system, and the method comprises the steps: constructing a radar signal RD image data set under an interference condition, and dividing the radar signal RD image data set into a training sample and a test sample; constructing an attention-enhanced ShuffleNet recognition model, and setting a loss function of a classification task of the attention-enhanced ShuffleNet recognition model; training a ShuffleNet recognition model of which the attention is enhanced by utilizing the training sample; and inputting a test sample into the trained attention-enhanced ShuffleNet recognition model, predicting and outputting a test sample category and a confidence score, and completing radar signal RD image interference recognition. The attention enhancement module is introduced, interaction between feature channels is enhanced from the channel information interaction level, the feature discrimination is improved, and therefore the RD image recognition precision of the image radar signal under interference is improved.

Description

technical field [0001] The invention belongs to the technical field of radar signals, in particular to a radar signal RD image interference identification method and system based on improved ShuffleNet. Background technique [0002] The RD image interference identification of radar signal is aimed at identifying the interference type of the interfered radar signal. Traditional interference identification methods include interference identification algorithms based on maximum likelihood criterion and interference identification algorithms based on feature extraction. These methods require manual analysis and feature extraction and rely heavily on domain prior and expert experience. Rigid, and the level of automation and intelligence is low, the generalization ability is weak, and it is difficult to adapt to the ever-changing complex confrontation environment. [0003] In recent years, radar signal interference identification has generally adopted methods based on deep learni...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/40G06K9/62G06N3/04
CPCG06N3/045G06F18/214G06F18/241
Inventor 张向荣王冠淳罗双才唐旭陈璞花张庆匡宏印
Owner XIDIAN UNIV
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