Source number estimation based on support vector machine
Yuping Zhang · Hebei ke-ji daxue xuebao · 2011
This paper proposed a source number estimation algorithm based on support vector machine(SVM) for improving estimation performance in low ratio of signal to noise,small snapshots and color noise environment.This algorithm decomposes the received signal data covariance matrix to get the signal vector and the noise vector at first,and then abstracts the property sort of signal and noise with Gerschgorin circle algorithm by the orthotropic property of the antenna array manifold and the noise vectors.At last,the algorithm constructs and trains the SVM to get the number of the incidence signals.The paper compares the algorithm with some classic algorithms by simulation experiment in low ratio of signal to noise,small snapshots and color noise environment,and results show that the algorithm has higher precision than that of classic algorithms.