Frequency and 2D Angle Estimation Based on a Sparse Uniform Array of Electromagnetic Vector Sensors
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Frequency and 2D Angle Estimation Based on a Sparse Uniform Array of Electromagnetic Vector Sensors Fei Ji1 and Sam Kwong2 1 School
of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China of Computer Science, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
2 Department
Received 25 April 2005; Revised 25 January 2006; Accepted 29 January 2006 Recommended for Publication by Joe C. Chen We present an ESPRIT-based algorithm that yields extended-aperture two-dimensional (2D) arrival angle and carrier frequency estimates with a sparse uniform array of electromagnetic vector sensors. The ESPRIT-based frequency estimates are first achieved by using the temporal invariance structure out of the two time-delayed sets of data collected from vector sensor array. Each incident source’s coarse direction of arrival (DOA) estimation is then obtained through the Poynting vector estimates (using a vector crossproduct estimator). The frequency and coarse angle estimate results are used jointly to disambiguate the cyclic phase ambiguities in ESPRIT’s eigenvalues when the intervector sensor spacing exceeds a half wavelength. Monte Carlo simulation results verified the effectiveness of the proposed method. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
1.
INTRODUCTION
The localization of source signals using vector sensor data processing has attracted significant attentions lately. Many advantages of using the vector sensor array have been identified and many array data processing techniques for source localization and polarization estimation using vector sensors have been developed. Nehorai and Paldi developed the Cram´er-Rao bound (CRB) and the vector cross-product DOA estimator using the vector cross product of the electricfield and the magnetic-field vector estimates [1, 2]. Li [3] developed ESPRIT-based angle and polarization estimation algorithm using an arbitrary array with small loops and short dipoles. Identifiablity and uniqueness study associated with vector sensors were done by Hochwald and Nehorai [4], Ho et al.[5] and Tan et al. [6]. Hochwald and Nehorai [7] studied parameter estimations with application to remote sensing by vector sensors. Ho et al. [8] developed a high-resolution ESPRIT-based method for estimating the DOA of partially polarized sources. Ho et al. [9] further studied the DOA estimation with vector sensors for scenarios where completely and incompletely polarized signals may coexist. Wong [10] has showed that the vector cross-product DOA estimator remains fully applicable for a pair of dipole triad and loop triad spatially displaced by an arbitrary and unknown distance
(rather than being collocated). Uni-vector-sensor ESPRIT is first presented to estimate 2D DOA and the polarization states of multiple monochromatic noncoherent incident sources using a single electromagnetic vector sensor by Wong and Zoltowski [11]. Nehorai and Tichavsky [12] presented an adaptive cross-product algorithm for tracking the direction t
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