Abstract
In this paper, a new array structure of sparse nested array (SNA) for electromagnetic vector sensor is designed. An electromagnetic vector sensor is composed of six spatially colocated, orthogonally oriented, diversely polarized antennas, which can measure three-dimensional electric and magnetic field components. By introducing sparse factor (SF) between every adjacent sensor, the proposed SNA has flexibility of extending the array aperture and reducing the mutual coupling effect. Meanwhile, a low-complexity multiparameter estimation algorithm is proposed for SNA. First, the vectorization operation for array manifold ensures the large degrees of freedom for multiparameter estimation, where the initial coarse estimates decrease search range. In addition, the improved off-grid orthogonal matching pursuit method obtains joint direction of arrival (DOA) and polarization estimates with a relatively small overcomplete dictionary because this off-grid method achieves high performance even if the estimates do not fall on the grid of the dictionary. Theoretical analysis and simulation results verify the superiority of the proposed array structure and the algorithm.
Highlights
Vector sensors, which are able to detect multiple physical components of the signals, have been widely used in array signal processing [1,2,3]
MUSIC (Multiple Signal Classification) algorithm is transformed for electromagnetic vector sensor array (EVSA) in [9], where the joint direction of arrival (DOA) and polarization estimates are measured by peak search
We perform some simulations in order to confirm the superior performance of the proposed sparse nested array (SNA) and the OGOMPbased algorithm. is section is divided into 4 parts
Summary
Vector sensors, which are able to detect multiple physical components of the signals, have been widely used in array signal processing [1,2,3]. Vector sensor arrays can obtain joint estimates of multiple parameters, such as electromagnetic vector sensor array (EVSA). EVSA can measure DOA and polarization information at the same time because vector sensor structure has the reception access of vector signals. Various DOA and polarization estimation algorithms are proposed for EVSAs, where most of them are inspired by the algorithms for scalar arrays. ESPRIT- (Estimating Signal Parameter via Rotational Invariance Techniques-) based algorithm is proposed in [7, 8], estimating both the arrival angles and the polarizations of incoming narrow-band signals with invariance properties of the EVSA. MUSIC (Multiple Signal Classification) algorithm is transformed for EVSA in [9], where the joint DOA and polarization estimates are measured by peak search. [11] proposes a novel rank reduction method for DOA, range, and polarization estimation, but near-field signal hypothesis is limited
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