Two-dimensional angle and polarization estimation using the ESPRIT algorithm

Li, J.; Compton, R.T.

doi:10.1109/8.142630

Cited by 114 publications

(17 citation statements)

References 9 publications

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“…In 1981, R.T. Compton put forward an adaptive signal processing method of the tripole antenna array, which can obtain better anti-disturbance performance than traditional array processing methods [5]. In 1992, J. Li et al introduced the rotational invariance techniques (ESPRIT) algorithm to the signal processing of the EMVS array to present a joint estimation algorithm of the AOA-polarization parameter [6]. In 1994, A. Nehorai and E. Paldi studied the received signal model of the EMVS array and CRB analysis of the parameter estimation comprehensively, in which the mean square angular error (MSAE) and the covariance vector angular error (CVAE) were introduced [7].…”

Section: Introductionmentioning

confidence: 99%

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

Gao

Gui

Xie

et al. 2017

Sensors

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This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank-false(L1,L2,·false) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method.

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Section: Introductionmentioning

confidence: 99%

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

Gao

Gui

Xie

et al. 2017

Sensors

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“…The problems of estimating frequency and two dimensional direction-of-arrivals (DOA) multiple cochannel signals have been considered in various works [2][3][4][5][6]. In [2], DOA matrix method can be used to estimate The research is supported by National Natural Science Foundation (NO.…”

Section: Introductionmentioning

confidence: 99%

“…60002002) two dimensional directions as long as either of dimensional parameter have no the same element. In [3][4][5][6], the ratios of eigenvalues method are used to automatically pair frequency, two spatial angle and polarization based on the square array of crossed dipoles; however, the automatic pairing method becomes more complicated with the increasing of the number of the estimated parameters.…”

Section: Introductionmentioning

confidence: 99%

Joint Frequency, Two Dimensional Arrival Angles Estimations via Marked Signal Subspace

Jia

Mao

Song

2006

2006 8th International Conference on Signal Processing

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It is essential for an efficient frequency and 2-D arrival angles in array signal processing. 3-D ESPRIT for joint 2-D angle and carrier frequency estimation offers an efficient way to handle the problem. Automatic pairing of the 3-D estimates is achieved via a marked subspace. This paper exploits multiple invariance matrix pencils from parallel uniform linear array to estimate a set of unknown parameters. For many frequency estimation and directions finding, all diagonal elements of invariance matrix are located on the unit circle in the complex plane. The marked subspace technique makes the set of parameter of each radiating source locate on the circle of the same radius, whereas different sources are located on different radius circle, so that several sources can automatically pair with the marker-radius. Computer simulations are shown to be in close agreement with theoretical analysis.

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“…1, where M = 8). Assuming N signals arrive at the array, as mentioned in [17,18], the ith column vector of A in (2) becomes: where ⊗ represents the Kronecker product, γ i and η i are the polarization parameters of ith signal, and a S (θ i , ϕ i ) is the steering vector of the ith signal on behalf of its spatial direction, written as:…”

Section: Polarization Musicmentioning

confidence: 99%

“…The polarization sensitive array is introduced into DOA estimation by Nehorai and Li [16,17]. In [17,18], Jian Li integrated the polarization into ESPRIT successfully. The pencil-MUSIC algorithm is devised for DOA and polarization estimation in [19,20,21], which extend the ESPRIT-like algorithm to partially polarized sources.…”

Section: Introductionmentioning

confidence: 99%

A Fast DOA Estimation Algorithm Based on Polarization MUSIC

Guo¹,

Mao²,

Li³

et al. 2015

RADIOENGINEERING

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Abstract.A fast DOA estimation algorithm developed from MUSIC, which also benefits from the processing of the signals' polarization information, is presented. Besides performance enhancement in precision and resolution, the proposed algorithm can be exerted on various forms of polarization sensitive arrays, without specific requirement on the array's pattern. Depending on the continuity property of the space spectrum, a huge amount of computation incurred in the calculation of 4-D space spectrum is averted. Performance and computation complexity analysis of the proposed algorithm is discussed and the simulation results are presented. Compared with conventional MUSIC, the proposed algorithm has considerable advantage in aspects of precision and resolution, with a low computation complexity proportional to a conventional 2-D MUSIC.

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Two-dimensional angle and polarization estimation using the ESPRIT algorithm

Cited by 114 publications

References 9 publications

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

Joint Frequency, Two Dimensional Arrival Angles Estimations via Marked Signal Subspace

A Fast DOA Estimation Algorithm Based on Polarization MUSIC

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