“Vector Cross-Product Direction-Finding” With an Electromagnetic Vector-Sensor of Six Orthogonally Oriented But Spatially Noncollocating Dipoles/Loops

Wong, Kainam Thomas; Yuan, Xin

doi:10.1109/tsp.2010.2084085

Cited by 129 publications

(153 citation statements)

References 38 publications

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“…The proposed array geometry is a sparse array with inter-sensor spacings far larger than a half-wavelength. Similar sparse vector-sensor arrays have been investigated in [10,11,36,45].…”

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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“…The proposed array geometry is a sparse array with inter-sensor spacings far larger than a half-wavelength. Similar sparse vector-sensor arrays have been investigated in [10,11,36,45].…”

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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“…Also note that the vector cross product estimator has been widely used for direction finding with a singlevector sensor [2,3,7]. However, this estimator cannot be exploited directly in the presence of mutual coupling among the vector sensor components.…”

Section: Remarksmentioning

confidence: 99%

“…An EMVS can therefore measure all the six electromagnetic field components induced by any electromagnetic incidence. After Li [1], and Nehorai and Paldi [2] first introduced the EMVS measurement model to the signal processing community, a variety of studies regarding signal processing with a single EMVS [2][3][4][5][6][7][8] have been extensively carried out. These methods ignore the mutual coupling across the six antenna component, which ultimately destroys the underlying model assumptions needed for their efficient implementations.…”

Section: Introductionmentioning

confidence: 99%

Direction finding with a single spatially stretched vector sensor in the presence of mutual coupling

Shu

Wang

et al. 2018

EURASIP J. Adv. Signal Process.

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This paper is concerned with DOA estimation using a single-electromagnetic vector sensor in the presence of mutual coupling. Firstly, we apply the temporally smoothing technique to improve the identifiability limit of a single-vector sensor. In particular, we establish sufficient conditions for constructing temporally smoothed matrices to resolve K > 2 incompletely polarized (IP) monochromatic signals with a single-vector sensor. Then, we propose an efficient ESPRIT-based method, which does not require any calibration signals or iterative operations, to jointly estimate the azimuth-elevation angles and the mutual coupling coefficients. Finally, we derive the Cramér-Rao bound (CRB) for the problem under consideration.

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“…Many other direction finding methods using a single vector sensor or arbitrarily spaced vector sensor arrays were proposed in [5-17, 34, 35, 37]. Such a six-component electromagnetic vector sensor has many advantages of direction-of-arrival (DOA) estimates, which were summarized by Wong & Yuan [17]. Besides, an "incomplete" EMVS such as tripole and crossed dipole comprises only a subset of the above-mentioned six EMVS and is of great interest in some practical applications [28, 29, 31-33, 36, 38].…”

Section: Electromagnetic Vector Sensormentioning

confidence: 99%

“…Various approaches for scalar antenna arrays' mutual-coupling calibration have been developed, and they can easily be found in the open literature [18][19][20][21][22][23][24][25]. Wong & Yuan used spatially noncollocating six-component EMVS to decreases the mutual coupling across the six collocated antennas [17]. However, there are few literatures on mutual coupling calibration methods for vector sensor or vector sensor array.…”

Section: Mutual Coupling Across the Six Collocated Antennas Of An Emvsmentioning

confidence: 99%

Mutual Coupling Calibration for Electromagnetic Vector Sensor

Wang

Wang²,

Zeng³

2013

PIER B

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Abstract-A subspace self-calibration ESPRIT algorithm for mutual coupling across an electromagnetic vector sensor is proposed in this paper. By introducing an auxiliary array element, the mutual coupling is calibrated. The whole array's mutual coupling matrix can be obtained simultaneously. A mathematic model for mutual coupling across the six collocated antennas of an electromagnetic vector sensor is established. And the solution of mutual coupling matrix was transformed into the solution of several matrix elements. The CramerRao Bound (CRB) is also derived in the end of this paper to verify the efficacy of the proposed algorithm. The simulation results demonstrate that this approach is correct and effective.

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“Vector Cross-Product Direction-Finding” With an Electromagnetic Vector-Sensor of Six Orthogonally Oriented But Spatially Noncollocating Dipoles/Loops

Cited by 129 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

Direction finding with a single spatially stretched vector sensor in the presence of mutual coupling

Mutual Coupling Calibration for Electromagnetic Vector Sensor

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