Subscribe Now Subscribe Today
Science Alert
Curve Top
Information Technology Journal
  Year: 2014 | Volume: 13 | Issue: 4 | Page No.: 725-729
DOI: 10.3923/itj.2014.725.729
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

A Novel Radar Emitters Scheme Recognition Algorithm using Support Vector Machine (SVM)

Qiang Liu

This study proposed an efficient radar emitter signal scheme recognition method using a novel one-class Support Vector Machine (SVM) based Bayesian classification algorithm. First, it is proven that the solution of one-class SVM using the Gaussian kernel can be normalized as an estimate of probability density and the probability density is used to construct the two-class and multi-class Bayesian clusters. The statistical characterization parameters of the multi radar emitter signals are extracted as the input feature vectors of the one-class SVM. Simulation result showed that the correct emitter scheme classification probability of the proposed classifier is comparable to traditional multi-class SVM classifier and better than the Artificial Neural Networks (ANN) based method. However, in the condition of large emitter mod class amount and large amount of training samples of each emitter signal class, the calculation amount of training and storage is only 0.5% of the traditional SVM classifier, which lead to less training time for the new classifier. In a word, the new mod scheme recognition method can be widely used in signal recognition field.
PDF Fulltext XML References Citation Report Citation
  •    A Study on Radar Emitter Recognition Based on SPDS Neural Network
How to cite this article:

Qiang Liu , 2014. A Novel Radar Emitters Scheme Recognition Algorithm using Support Vector Machine (SVM). Information Technology Journal, 13: 725-729.

DOI: 10.3923/itj.2014.725.729






Curve Bottom