DOA Estimation of Completely Polarized Signals by One-Bit Cross-Dipole Arrays

The one-bit cross-dipole array employs one-bit quantization to reduce the sampling system overhead while extracting polarization information from electromagnetic signals, thereby lowering the system complexity of the polarization array. However, the existing DOA estimation algorithms for this array utilize incomplete information from the received signals of the array. Cross-dipole array consists of two scalar arrays orthogonal to each other. With one-bit measurements, the array outputs two one-bit scalar array datum. By exploiting the two array datum, we can generate two covariance matrices and two cross-covariance matrices of the cross-dipole array signals. Existing direction-of-arrival (DOA) estimation algorithms based on one-bit measurements only realize DOA estimation by combining two covariance matrices, resulting in insufficient mining of information. In this paper, we propose a DOA estimation method for completely polarized signals that jointly utilizes auto-covariance and cross-covariance. To do this, we first study the reconstruction of two cross-covariance matrices from one-bit measurements. Based on the analyses of four covariance matrices, we then formulate virtual array datum consisting of four virtual snapshots by difference array technique, called parallel coarray signals. As the parallel coarray signals are coherent although the incoming sources are independent, we employ the spatial-smoothing technique on the parallel coarray signals to perform the DOA estimation. Numerical results show that the performance of the proposed method is significantly improved for completely polarized signals.