Self-initiating MUSIC-based direction finding and polarization estimation in spatio-polarizational beamspace

Wong, Kainam Thomas; Zoltowski, M.D.

doi:10.1109/8.884492

Cited by 164 publications

(6 citation statements)

References 38 publications

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“…Wong et al advanced the "vector-cross-product" direction-finding algorithm by investigating some novel capabilities of the electromagnetic vector-sensor (array), for example, sparse array with six-component electromagnetic vector-sensor [10], DOA estimation without the priori known sensors' locations [9], "self-initiating MUSIC" [12] and blind geolocation, beamforming for frequency-hopping sources of unknown and arbitrary hop-sequences [13].…”

Section: Introductionmentioning

confidence: 99%

Enhanced "vector-cross-product" direction-finding using a constrained sparse triangular-array

Yuan

2012

EURASIP J. Adv. Signal Process.

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A new configuration of sparse array is proposed in this article to estimate the direction-of-arrivals (DOAs) and polarizations of multiple sources. This constrained sparse array is composed of a dipole-triad, a loop-triad, and a single antenna, which can be a dipole, a loop, or a scalar-sensor. These three units comprise a triangular geometry in the space. This geometry creatively synergizes the conventional interferometry method based on the spatial phase-delay across displaced antennas, and the "vector-cross-product" based on Poynting-vector estimator to enhance the DOA estimation accuracy. The investigated algorithm based on this configuration adopts the "vectorcross-product" DOA estimator to provide the coarse estimate and then derives the fine estimate by extracting the inter-sensor phase factors in the sparse array. Following this, the disambiguation approach is adapted to derive the unambiguous estimate, and this estimate is also fine in estimation resolution. The proposed configuration can extend the array aperture and also reduce the mutual coupling. The significant performance of the proposed sparse array composition is demonstrated by Monte Carlo simulations when the inter-sensor spacing far exceeds a half-wavelength.

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Section: Introductionmentioning

confidence: 99%

Enhanced "vector-cross-product" direction-finding using a constrained sparse triangular-array

Yuan

2012

EURASIP J. Adv. Signal Process.

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“…Thus, the damaged sensors can produce bad data, which means that the effective signal information cannot be received by the impaired sensors. As we all know, traditional subspace methods, such as MUSIC [ 6 , 7 , 8 , 9 ] and ESPRIT [ 10 , 11 ], were proposed under the assumption of an intact array structure, and the performance of the above methods highly depends on an accurate correlation matrix structure. If the array output structure information is corrupted, and especially if bad data exist, the DOA estimation performance will dramatically degrade or even fail.…”

Section: Introductionmentioning

confidence: 99%

Robust Tensor-Based DOA and Polarization Estimation in Conformal Polarization Sensitive Array with Bad Data

Lan,

Jiang,

et al. 2024

Sensors

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Partially impaired sensor arrays pose a significant challenge in accurately estimating signal parameters. The occurrence of bad data is highly probable, resulting in random loss of source information and substantial performance degradation in parameter estimation. In this paper, a tensor variational sparse Bayesian learning (TVSBL) method is proposed for the estimate of direction of arrival (DOA) and polarization parameters jointly based on a conformal polarization sensitive array (CPSA), taking into account scenarios with the partially impaired sensor array. First, a sparse tensor-based received data model is developed for CPSAs that incorporates bad data. Then, a column vector detection method is proposed to diagnose the positions of the impaired sensors. In scenarios involving partially impaired sensor arrays, a low-rank matrix completion method is employed to recover the random loss of signal information. Finally, variational sparse Bayesian learning (VSBL) and minimum eigenvector methods are utilized sequentially to obtain the DOA and polarization parameters estimation, successively. Furthermore, the Cramér-Rao bound is given for the proposed method. Simulation results validated the effectiveness of the proposed method.

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“…The electromagnetic vector sensor array is a new type of array due to its polarization diversity [9,18,19]. Vector sensors are already commercially available, for example, from Flam and Russell, Inc., Horsham, PA [20,21], and from EMC Baden, Inc., Baden, Switzerland.…”

Section: Introductionmentioning

confidence: 99%

Estimating DOA and polarization with spatially spread loop and dipole pair array

Wang

Chen

Wang

et al. 2015

J. of Syst. Eng. Electron.

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The nonuniform L-shaped spatially spread loop and dipole (SSLD) array whose inter-element spacing is greater than half a wavelength is studied. A joint parameter estimation algorithm of direction of arrival (DOA), frequency and polarization is presented for plane-wave signals. The direct sampling and the corresponding delayed sampling data are used to construct the data correlation matrix. On the basis of the subspace theory and the least square method, the frequency and the steering vector of the whole array are obtained. According to the relationship of the array manifold vector between electric dipoles and magnetic loops, the polarization parameters are given. The unambiguous phase estimates are acquired by applying virtual baseline array transformation to the spatial steering vectors, and they are used as coarse references to disambiguate the cyclic phase ambiguities in phase differences between two adjacent array elements on the array, then the high accuracy DOA estimates are obtained. Closed-form solutions for each parameter are obtained. This method has advantages of lower calculation complexity and no parameter matching. The experiment results verify the effectiveness and feasibility of the presented algorithm.

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Self-initiating MUSIC-based direction finding and polarization estimation in spatio-polarizational beamspace

Cited by 164 publications

References 38 publications

Enhanced "vector-cross-product" direction-finding using a constrained sparse triangular-array

Enhanced "vector-cross-product" direction-finding using a constrained sparse triangular-array

Robust Tensor-Based DOA and Polarization Estimation in Conformal Polarization Sensitive Array with Bad Data

Estimating DOA and polarization with spatially spread loop and dipole pair array

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