Title :
Source number estimation methods base on suooprt vector machine algorithm
Author :
Hui-qiang, Zhao ; Zhao Bo ; Houde, Quan ; Yu-ping, Zhang
Author_Institution :
Dept. of Electron. Eng., Ordnance Eng. Coll., Shijiazhuang, China
Abstract :
The source number estimation is a basic problem in the smart antenna technology. Some classic estimation algorithms have been developed in past twenty years like `AIC´, `MDL´, hypothesis test (`HPY´), Gerschgorin Radii (`GDE´), etc .But the estimation error will be great in the circumstances of low S/N, small sample with these algorithms. This paper develops a novel method based on support vector machine (SVM), which offers more precise result than these classic algorithms .The novel algorithm extracts several classification characteristic vectors from the data matrix received by the array with GDE at first, and then constructs and trains the SVM, gets signal subspace from the output of the SVM and sources signal number from the number of vectors of the signal subspace. The simulation result confirms the conclusion.
Keywords :
adaptive antenna arrays; signal sources; support vector machines; characteristic vectors; data matrix; gerschgorin radii; smart antenna technology; source number estimation method; support vector machine algorithm; Antenna arrays; Colored noise; Covariance matrix; Data mining; Gaussian processes; Sensor arrays; Signal to noise ratio; Support vector machine classification; Support vector machines; Transmission line matrix methods; Gerschgorin Radii; SVM; Source number estimation; characteristic vector;
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
DOI :
10.1109/PACIIA.2009.5406439