Performance Comparisons of Eigenstructure Based Spatial Spectrum Estimation Algorithms in a Multipath Environment

다경로인 경우 Eigen 구조를 이용하는 공간 스펙트럼 추정 알고리듬의 성능비교

The purpose of this paper is to explain eigenstructure based spatial spectrum estimation algorithms computing better estimates than the other approaches. Also, as an approach to overcome performance degradations in a multipath environments, the notion of forward and backwark spatial smoothing is discussed. Intensive simulation results,which include the comparisons of the eigenbased spatial spectral estimation algorithms in the situations of faulty estimation of the number of signals, are presented. The simulation results have shown that overestimation of the number of signals is more desirable than underestimation in using EV (Eigen Vector) and MUSIC (Multiple Signal Classification) algorithms and that underestimation of the number of signals is better strategy than overestimation in using eigenstructure based LP(Linear Prediction) algorithms.