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Research of Unknown Radar Signal Sorting Algorithm

Author: XiangZuo
Tutor: TangJianLong
School: Xi'an University of Electronic Science and Technology
Course: Circuits and Systems
Keywords: Signal sorting PRI sorting Grid Density Clustering Support Vector Clustering
CLC: TN957.51
Type: Master's thesis
Year: 2011
Downloads: 133
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Abstract


The radar signal sorting system is an integral part of radar signal processing system , and has become an extremely important factor in modern warfare . Sorting through the radar signal , able to accurately identify the various space radar and their parameters , and in order to do further processing into the radar library , such as positioning , tracking and analysis . However, with the rapid development of radar signal generation technology , processing technology , the new radar system replacing the traditional conventional pulsed radar , radar signal environments become increasingly complex and volatile . How to correct radar signal sorting in increasingly complex radar signal environment has become the focus of attention at home and abroad . This paper first introduces the the radar signals PRI sorting algorithms , and the advantages and disadvantages of each algorithm briefly described . PRI sorting algorithms including : dynamic correlation method , histogram method (CDIF Act , SDIF Act ) the PRI transform method , plane transform method . Next, in order to achieve the correct sorting of the new system of radar signals for traditional PRI sorting algorithm lack of clustering algorithm is applied to the area of radar signal sorting , and introduced two suitable the unknown emitter signal separation algorithm : mesh density - based clustering radar signal sorting algorithm based on improved support vector clustering radar signal sorting algorithms . Mesh density clustering algorithm meshing technology , to form a grid cell ; stream mapping to each grid cell and then pulse signal pulse descriptor word (PDW) , and the grid density based clustering , in order to achieve pulse flow sorting . Improved support vector clustering algorithm to generate a correlation matrix instead of the original sample points on the basis of the original support vector clustering (SVC) algorithm using support vector clustering identification stage point (SVs) , effective in reducing the incidence matrix scale ; then using the depth-first search algorithm to search the incidence matrix generate initial clustering results ; initial clustering results using combined similar cluster centers algorithm to obtain the optimal clustering classification results , thus effectively alleviate kernel function parameter q clustering results . Simulation results prove : even in a complex environment , we propose two algorithms can achieve better separation effect .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radar > Radar equipment,radar > Radar receiving equipment > Radar signal detection and processing
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