DocumentCode :
3696051
Title :
Research on Object Self-Organizing Iterative Cluster Algorithm of Emitter Identification
Author :
Xiaoxuan Wang;Lianwang Diao;Xin Xu
Author_Institution :
Sci. &
Volume :
1
fYear :
2015
Firstpage :
487
Lastpage :
490
Abstract :
A novel sorting algorithm based on clustering is proposed to resolve problems such as low sorting precision and even failure which are caused by conventional radar signal sorting algorithm applied in present high-density signal environment. According to the characters of electromagnetic parameters, the advantages and disadvantages of the traditional clustering algorithms in data mining have been discussed in this paper. By using traditional clustering algorithm, users have to specify in advance how many clusters are being sought and it cannot be processed well if signal samples are not in spherical cluster distribution. An improved clustering algorithm based on self-organizing iterative analytic is presented in this paper, which avoid relying on prior knowledge or depending on signals´ distribution. Simulation result proves the validity and practicability of this algorithm. It provides a new way for object clustering problem in emitter identification.
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2015 7th International Conference on
Print_ISBN :
978-1-4799-8645-3
Type :
conf
DOI :
10.1109/IHMSC.2015.21
Filename :
7334752
Link To Document :
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