Multiple parameters joint estimation via single signal subspace
Jianshe Song · Chinese Journal of Radio Science · 2007
The eigenvalues estimation and association of subspace rotation invariance is an improtant problem in the multidimensional spectral and array processing.This paper exploits multiple invariance subspace of the second-order statistic of the observations collected from parallel crossed dipoles uniform linear array,and automatically paired frequency,two-dimensional directions and the polarization of incoming narrow-band signals via single signal subspace as long as each signal parameters are unique.The algorithm provides multiple parameter estimation via single eigenvector matrix that neither requires any expensive search procedure nor any other pairing strategy.Moreover it does not break down if several independent signals have common parameters.The Monte Carlo simulations are shown to be in close agreement with theoretically analysis.