Cramér-Rao bound for multiple parameters estimation using a polarization sensitive array

In this paper, new Cramér-Rao lower bounds （CRB） of the estimates of frequencies, two-dimensional arrival angles and polarization parameters of multiple incident signals are derived for a polarization sensitive array. The incident sources have distinct carrier-frequencies, in contrast to the modeling of all sources to be at the same known carrier-frequency, which has been investigated in the existing research literature on the Cramér-Rao bounds （CRB） for polarization sensitive direction finding. The derived CRBs are compact closed-form expressions and applicable to an arbitrary array geometry. Numerical examples and analysis of some special cases provide insights into the fact that the estimation accuracy of all parameters is enhanced with the increasing signal-to-noise ratio （SNR） and number of snapshots. In addition, they are hardly influenced by the sampling frequency and independent of the initial phase of incident sources. These insights offer guidelines to the system engineer on how to improve parameters＇ estimation accuracy.

DOA and polarization estimation via signal reconstruction with linear polarization-sensitive arrays

This paper addresses the problem of direction-of-arrival （DOA） and polarization estima- tion with polarization sensitive arrays （PSA）, which has been a hot topic in the area of array signal processing during the past two or three decades. The sparse Bayesian learning （SBL） technique is introduced to exploit the sparsity of the incident signals in space to solve this problem and a new method is proposed by reconstructing the signals from the array outputs first and then exploit- ing the reconstructed signals to realize parameter estimation. Only 1-D searching and numerical calculations are contained in the proposed method, which makes the proposed method computa- tionally much efficient. Based on a linear array consisting of identically structured sensors, the proposed method can be used with slight modifications in PSA with different polarization structures. It also performs well in the presence of coherent signals or signals with different degrees of polarization. Simulation results are given to demonstrate the parameter estimation precision of the proposed method.

Joint frequency,2-D DOA,and polarization estimation using parallel factor analysis

This paper proposes a new algorithm for joint frequency, two-dimensional （2-D） directions-of-arrival （DOA）, and polarization estimation using parallel factor （PARAFAC） analysis model and cumulant. The proposed algorithm designs a new array configuration, and extends the PARAFAC analysis model from the common data-domain and subspace-domain to the cumulant one, and forms three-way arrays by using the three cumulant matrices obtained from the properly chosen dipole outputs, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, and then jointly estimates the source parameters via the low-rank decomposition of the constructed PARAFAC model. In comparison with the conventional methods, the proposed method alleviates the aperture loss, and avoids pairing parameter. Finally, the simulation results are presented to validate the performance of the proposed method.