Title :
The Application of Unsupervised Clustering in Radar Signal Preselection Based on DOA Parameters
Author :
Zhu, Xiang-Peng ; Jin, Ming ; Qian, Wei-Qiang ; Liu, Shuai ; Wei, Yu-Mei
Author_Institution :
Harbin Inst. of Technol., Harbin, China
Abstract :
With the deterioration of electronic environment, using signals DOA (direction of arrival) parameters has great significance to preselect multiple radar pulses. Cluster analysis as an important means of data classification, is gradually applied to radar signal sorting. In this paper, a novel method of signal sorting flowsheet is proposed based on Fuzzy Clustering to sort emitters DOA as data objects, with dynamic clustering for reference and Gaussian distance function instead of Euclidean distance. This method avoids establishing enormous similar matrix and adapt to the change of the number of emitters. The result of simulation demonstrates that this method is effective.
Keywords :
Gaussian distribution; direction-of-arrival estimation; radar signal processing; unsupervised learning; DOA parameters; Gaussian distance function; cluster analysis; data classification; direction of arrival; multiple radar pulses; radar signal preselection; radar signal sorting; unsupervised clustering; Algorithm design and analysis; Azimuth; Classification algorithms; Clustering algorithms; Heuristic algorithms; Radar; Sorting; direction of arrival; fuzzy clustering; radar signal preselection;
Conference_Titel :
Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8043-2
Electronic_ISBN :
978-0-7695-4180-8
DOI :
10.1109/PCSPA.2010.236