Closed-form eigenstructure-based direction finding using arbitrary but identical subarrays on a sparse uniform Cartesian array grid

Zoltowski, M.D.; Wong, Kainam Thomas

doi:10.1109/78.852001

Cited by 179 publications

(121 citation statements)

References 7 publications

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“…This selects the th-subarray sector of as . (25) now produces the subarray manifold estimates, from which the th source's six electromagnetic-field components may be derived (36) (18) also becomes (37) The above modifications allow the proposed method to handle up to sources. If , then up to can be accommodated if the above array configuration of vectorsensors is viewed as identical but translated subarrays of irregularly spaced vector-sensors.…”

Section: Extension To Irregularly Spaced Subarrays Of Electromagnmentioning

confidence: 99%

“…Reference [10] is simplified in [35] and is extended in [27] for partially polarized sources. Reference [36] is first to use the vector cross-product DOA estimator in an ESPRIT-based direction finding scheme involving multiple vector sensors and is followed up by [32] and [37]. References [25], [28] apply the vector cross-product DOA-estimator in another ESPRIT-based with a solitary vector sensor.…”

Section: B Summary Of Relevant Literaturementioning

confidence: 99%

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

Wong

Zoltowski

2000

IEEE Trans. Antennas Propagat.

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164

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Abstract-A novel self-initiating multiple signal classification (MUSIC)-based direction-finding (DF) and polarization-estimation algorithm in spatio-polarizational beamspace is herein presented for an arbitrarily spaced array of identically oriented electromagnetic vector sensors. An electromagnetic vector sensor, already commercially available, is composed of six colocated, but diversely polarized, antennas distinctly measuring all six electromagnetic-field components of a multisource incident wave field. This proposed algorithm: 1) exploits the incident sources' polarization diversity; 2) decouples the estimation of the sources' arrival angles from the estimation of the sources' polarization parameters; 3) uses ESPRIT on pairs of vector sensors to self-generate coarse estimates of the arrival angles to start off its MUSIC-based iterative search without any a priori information on the incident sources' parameters; 4) estimate the sources' polarization states; and 5) automatically pairs the -axis direction-cosine estimates with the -axis direction-cosine estimates and with the polarization estimates. Monte Carlo simulation results verify the efficacy of the proposed method.

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Section: Extension To Irregularly Spaced Subarrays Of Electromagnmentioning

confidence: 99%

Section: B Summary Of Relevant Literaturementioning

confidence: 99%

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

Wong

Zoltowski

2000

IEEE Trans. Antennas Propagat.

Self Cite

164

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“…That means the array will have a large aperture, and result in an improper array configuration. It is well known that the uniform intersensor spacing beyond a halfwavelength will lead to a set of cyclically ambiguous of array manifold matrix [6,21,22]. Thanks to the circular symmetry, uniform circular array (UCA) in [23] and uniform concentric circular array (UCCA) in [24,25] are attractive antenna configurations in the context of DOA estimation.…”

Section: Introductionmentioning

confidence: 99%

A Joint Parameter Estimation Method With Conical Conformal CLD Pair Array

Wang¹

2015

PIER C

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Abstract-A novel direction of arrival (DOA) and polarization estimation method with sparse conical conformal array consisting of concentred loop and dipole (CLD) pairs along the z-axis direction is proposed in this paper. In the algorithm, the DOA and polarization information of incident signals are decoupled through transformation to array steering vectors. According to the array manifold vector relationship between electric dipoles and magnetic loops, the signal polarization parameters are given. The phase differences between reference element and elements on upper circular ring are acquired from the steering vectors of upper circular ring, it can be used to give rough but unambiguous estimates of DOA. The phase differences are also used as coarse references to disambiguate the cyclic phase ambiguities in phase differences between two array elements on lower circular ring. Without spectral peak searching and parameter matching, this method has the advantage of small amount of calculation. Finally, simulation results verify the effectiveness of the algorithm.

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“…A vector-sensor comprises two or more collocated different types of scalar-sensors and is generally advantageous over a scalar-sensor, eg, for an electromagnetic vectorsensor, it can additionally exploit the polarization difference among the received signals [19]. Traditionally the output of a vector-sensor array is preprocessed to be a long-vector [19][20][21][22][23][24][25][26][27], while several recent approaches utilize hypercomplex (eg, quaternion [18], bicomplex [28], biquaternion [29,30], quad-quaternion [31], Euclidean 3-space [32]) or tensorial (eg, fourth-order interspectral tensor [33]) models. The use of hypercomplex algebra provides a compact way of handling of the recorded data, and demonstrates its unique characteristics in reduced memory consumption and improved robustness to model errors [18].…”

Section: Introductionmentioning

confidence: 99%

User–Parameter–Free Robust Adaptive Beamforming Algorithm for Vector–Sensor Arrayswithin the Hypercomplex Framework

Gou¹,

Liu²,

Ma³

et al. 2013

Journal of Electrical Engineering

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The major flaw of the conventional diagonal loading (DL) method is that it is unclear to choose appropriate DL levels or user-parameters (UPs), though several remarkable contributions have been made to regularize model errors without UPs. An UP-free algorithm for two-component vector-sensor arrays, which is robust to steering vector errors, is considered. The algorithm is within the hypercomplex framework using quaternions, and the optimal solution is found at the maximal correlation between the quaternionic and complex outputs. The performance of the proposed beamformer is illustrated via numerical simulations and is compared with several other UP-free adaptive beamformers.K e y w o r d s: array signal processing, robust adaptive beamforming, vector-sensor, user-parameter-free, quaternion

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Closed-form eigenstructure-based direction finding using arbitrary but identical subarrays on a sparse uniform Cartesian array grid

Cited by 179 publications

References 7 publications

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

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

A Joint Parameter Estimation Method With Conical Conformal CLD Pair Array

User–Parameter–Free Robust Adaptive Beamforming Algorithm for Vector–Sensor Arrayswithin the Hypercomplex Framework

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