Radio frequency interference suppression and classification method based on convolutional neural network
A technology of convolutional neural network and suppression of interference, which is applied in the field of synthetic aperture radar signal processing, can solve the problems of difficult to meet the accuracy requirements and lack of system error, and achieve the effect of accurate classification and identification and filling the technical gap
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[0068] Example 1
[0069] The present invention provides a radio frequency suppression interference classification method based on convolutional neural network, including:
[0070] S1. Initialize the SAR system transmission signal parameters, target signal parameters and interference signal parameters, calculate the target signal and interference signal, superimpose the interference signal on the target signal to obtain the interfered echo signal, and mark the interference signal in each echo signal Types of interference; specifically include:
[0071] S11. Input the parameters of the SAR system transmission signal to the computer, including the transmission signal pulse width T=2.5μs, and the transmission signal modulation frequency K=2×10 13 Hz / s;
[0072] S12. Input target signal parameters to the computer, including sampling frequency f s =100MHz, the time width of the receiving window T w =10μs; the amplitude range a of the SAR complex image of the uniform scattering scene is a r...
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