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FM / radiation information fusion approach

Author: LiChunLong
Tutor: XuJianZhong
School: Nanjing University of Technology and Engineering
Course: Communication and Information System
Keywords: Wideband linear frequency modulated continuous wave radar Millimeter-wave DC full power radiometer Signal analysis Feature Extraction Information Fusion Neural Networks
CLC: TP202
Type: Master's thesis
Year: 2010
Downloads: 46
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Abstract


The topic for the FM / radiation information fusion method to study the problem of signal processing in the detection and recognition of the empty goal ( a certain type of fighter ) . Continuous wave radar chirp based broadband radiometer and millimeter-wave DC full power of the hardware system , its information fusion research . Broadband linear frequency modulated continuous wave radar and millimeter wave the DC full power radiometer analysis , for a certain type of fighter , calculate multi- scattering center model scattering points approximation radar cross section , and is established based on the actual geometry of the fighter radiation model . HRRP antenna temperature curve in the distance like a one-dimensional simulation broadband linear frequency modulated continuous wave radar multiple scattering center model and millimeter-wave DC full power radiometer antenna temperature curves were extracted by the wavelet analysis method the characteristic vector of the extracted feature vector with respect to the raw data to achieve a certain degree of data compression and noise immunity , and target recognition by BP network simulation proved the extraction of feature vectors can be a good target identification . Information fusion processing , two feature layer parameter template method and neural network - based information integration programs , and the characteristics of the system based on neural network layer information fusion do in-depth research . Characteristics of the system based on neural network layer information integration programs fusion , and target recognition simulation , two fusion methods achieve the same signal-to-noise ratio , improved target recognition rate , the fusion method B with respect to the fusion method a , reduce the amount of data to improve the real - time target identification .

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