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Passive radar external radiation source signal identification method based on transfer learning

A passive radar and external radiation source technology, applied to radio wave measurement systems, instruments, etc., can solve problems such as insufficient results and insufficient flexibility of the model, and achieve the effect of saving training time

Active Publication Date: 2018-09-07
TIANJIN UNIV
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Problems solved by technology

When traditional machine learning deals with tasks such as data distribution, dimensionality, and model output changes, the model is not flexible enough and the results are not good enough, while transfer learning relaxes these assumptions

Method used

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  • Passive radar external radiation source signal identification method based on transfer learning
  • Passive radar external radiation source signal identification method based on transfer learning
  • Passive radar external radiation source signal identification method based on transfer learning

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Embodiment Construction

[0024] The present invention aims to design a migration learning method for external radiation source signal recognition, which can solve the migration problem of models obtained by training signals with different sampling rates. This method is based on model-based parameter migration, which migrates the model and parameters trained on a sampling frequency dataset (source domain) to another sampling frequency dataset (target domain), requiring only a small amount of labeled target domain data. , after a short period of training, the recognition model of the target domain can be obtained. This method is independent of the size relationship between the sampling frequency of the source domain and the target domain.

[0025] (1) Model structure

[0026] The realization model of the present invention is as figure 1 shown.

[0027] Firstly, a model is trained on a sampling frequency dataset as the basic network, and then the model and parameters of the basic network are directly...

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Abstract

The invention belongs to the field of radar and communication signal identification and provides a transfer learning method for external radiation source signal identification. The transfer problem ofmodels obtained through training of different sampling rate signals can be solved. The method is not relevant to the sampling efficiency of a source domain and a target domain. Therefore, according to the adopted technical scheme, the passive radar external radiation source signal identification method based on transfer learning comprises the steps that one model is firstly trained on a samplingfrequency data set to serve as a basic network, then a model of the basic network and parameters are directly transferred to data set target domains having different sampling frequency, fine adjustment training is performed, and a neural network model including three layers of convolution and two whole connection layers is used for the basic network. The method is mainly applied to radar and communication signal identification occasions.

Description

technical field [0001] The invention belongs to the field of radar and communication signal identification and the field of transfer learning. Based on the trained deep learning model, a transfer learning-based signal recognition method for passive radar external emitters is designed. Background technique [0002] The complex and heterogeneous electromagnetic environment brings huge challenges to signal processing. It is urgent to develop technologies for special applications of military-civilian integration, public systems and dedicated systems, so as to effectively improve spectrum utilization efficiency, improve the environment, and coexist cooperatively. Therefore, the future radar system design must start from the perspective of improving the utilization of spectrum resources. Passive radar, waveform diversity, bionic design and cognitive methods are effective methods to solve spectrum congestion. [0003] Passive radar (also known as passive radar, external radiation ...

Claims

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Application Information

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IPC IPC(8): G01S7/02
CPCG01S7/021
Inventor 汪清杜攀非刘文斌贺爽
Owner TIANJIN UNIV
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