Abstract
In this paper, we investigate the problem of source localization and classification under the coexistence of both completely polarized (CP) and partially polarized (PP) electromagnetic (EM) signals, using a crossed-dipole sensor array. We propose a MUltiple SIgnal Classification (MUSIC)-based solution, which does not require multidimensional searches. Moreover, the proposed method need no estimation of the degree of polarization of signals. The efficacy of the proposed method is examined by comparing with existing methods.
Highlights
Estimation of arrival angles of multiple narrowband electromagnetic (EM) planewave signals is a key problem in many engineering applications including radar, wireless communications and seismic exploration
We see from the figure that the complete polarized (CP) estimator can provide the angle estimates of both the partially polarized (PP) and CP signals, while the PP estimator can only give the angle estimates of the PP signals
We have presented a MUltiple SIgnal Classification (MUSIC)-based method for angle estimation and signal classification under the simultaneous existence of completely polarized and partially polarized electromagnetic signals
Summary
Estimation of arrival angles of multiple narrowband electromagnetic (EM) planewave signals is a key problem in many engineering applications including radar, wireless communications and seismic exploration. These methods include MUltiple SIgnal Classification (MUSIC)-based algorithms [1,2,3], Estimation of Signal Parameter via Rotational Invariance Technique (ESPRIT)-based algorithms [4,5,6,7], subspace fitting based method [8], propagator-based method [9], and vector cross product based algorithms [10,11,12]. All the above mentioned algorithms are based on the assumption that the impinging signals are complete polarized (CP) In applications such as ionospheric and radar, signals are often partially polarized [19,20]. [23] considered the partially polarized signals be located in near-field, and presented the ML- and subpace-based algorithms. Throughout the paper, transpose, conjugate transpose, complex conjugate and pseudo inverse are denoted by superscripts T, H, ∗, and †, respectively. ⊗ represents the Kronecker-product operator, Im stands for a m × m identity matrix, and 0m,n is a m × n zero matrix
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