Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array
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Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array Xiaolong Su1 · Zhen Liu1
· Tianpeng Liu1 · Bo Peng1 · Xin Chen1 · Xiang Li1
Received: 17 December 2019 / Revised: 30 March 2020 / Accepted: 31 March 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In this paper, we employ the geometry of uniform circular array to achieve classification and localization of mixed near-field and far-field sources. Considering that the eigendecomposition of the covariance matrix requires high computational cost, we develop the propagator method to obtain the noise subspace and reduce complexity. Firstly, since the direction parameters of far-field sources at centrosymmetry sensors hold a conjugate structure while the covariance matrix of near-field sources holds a Hermitian structure, we exploit the covariance differencing approach to extract the pure near-field sources from mixed sources. Then, we improve the ESPRIT-like method and one-dimensional MUSIC method to determine the 2-D direction-of-arrival (DOA) and range of near-field sources, respectively. Finally, by calculating the noise power of mixed sources, we utilize the oblique projection approach to extract the pure far-field sources and exploit the 2-D MUSIC method to determine the 2-D DOA of far-field sources. Simulations demonstrate that the proposed algorithm can avoid the pseudo-peaks in the 2-D DOA spatial spectrum of far-field sources and provide the satisfactory performance of mixed source localization.
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Zhen Liu [email protected] Xiaolong Su [email protected] Tianpeng Liu [email protected] Bo Peng [email protected] Xin Chen [email protected] Xiang Li [email protected]
1
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
Circuits, Systems, and Signal Processing
Keywords Mixed sources · Uniform circular array · Propagator method · Covariance differencing · ESPRIT-like · Oblique projection
1 Introduction Passive localization of mixed sources is a branch of array signal processing, which has been developed and applied in the fields of communication, radar, sonar, seismic exploration and radio astronomy [24, 30, 34]. The far-field sources impinging on the array are considered as plane waves which require direction-of-arrival (DOA) estimation, while the near-field sources are described as spherical waves which require DOA as well as range estimation [25, 27]. By employing the geometry of uniform linear array (ULA) and the principle of rank reduction (RARE), the cocentered orthogonal loop and dipole (COLD) antennas are used to estimate the joint DOA, range and polarization of the near-field rectilinear sources [2]. Recently, numerous researches have employed the geometry of ULA for localization of mixed near-field sources and far-field sources [6, 10, 15, 17, 29]. By dividing the geometry of ULA into two subarrays, Wang et al. [21] exploited the fourth-order cumulant matrices to re
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