Sharif Digital Repository

In this paper, we present a method for estimating the signal sources steering vector using an arbitrary planar array with omnidirectional elements. The proposed method improves the initial estimation of the signal steering vector in two steps. In the first step of this algorithm we minimize of the distance between the steering vector and the signal subspace. The second step improves the estimation of the first step using a defined cost function which is based on a structural criterion for signal steering vector. Simulation results show the capability of the proposed signal steering vector estimate improvement  

This paper uses the shift-invariance property of uniform linear array in root-MUSIC estimator for obtaining signal and noise subspaces by applying multistage Wiener filter (MSWF) procedure. Also, the MSWF root-MUSIC based on the pseudo-noise resampling process for estimating the direction of arrival (DOA) of signals is proposed. By this process, a root estimator bank and a corresponding DOA estimator bank are constructed. Then, a hypothesis test is applied to the DOA estimator bank to detect the normal DOA estimators from abnormal DOA estimators called outliers. By averaging the corresponding root estimators of normal DOA estimators, the final DOAs can be determined more accurately. When all... 

This study presents a method based on minimum description length criterion to enumerate the incident waves impinging on a large array using a relatively small number of samples. The proposed scheme exploits the statistical properties of eigenvalues of the sample covariance matrix (SCM) of Gaussian processes. The authors use a number of moments of noise eigenvalues of the SCM in order to separate noise and signal subspaces more accurately. In particular, the authors assume a Marcenko-Pastur probability density function (pdf) for the eigenvalues of SCM associated with the noise subspace. We also use an enhanced noise variance estimator to reduce the bias leakage between the subspaces....