Regularized matrix method for near-field diagnostic techniques of phased array antennas

Gattoufi, L.; Picard, Dominique; Samii, Y. Rahmat; Bolomey, Jean-Charles

doi:10.1109/aps.1997.631741

Cited by 6 publications

(9 citation statements)

References 8 publications

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“…In order to circumvent this difficulty, Golub et al [14] proposed an extension of the heuristic technique introduced by Allen in [19]. This extension, referred to as GCV, was used successfully in several applications including the determination of current sources from NF measurements [5]. With our notations, the GCV value for is defined as …”

Section: Generalized Cross Validation For Estimation Ofmentioning

confidence: 99%

“…But, to our knowledge, none of them specifically showed how regularization could help to recover equivalent currents from NF measurements. Gattoufi et al [5] proposed to use Tikhonov regularization to retrieve equivalent currents on a radiating phased array antenna. However, very few numerical results were provided to demonstrate the validity of the method, and the choice of the regularization matrix was limited to the identity matrix.…”

Section: Introductionmentioning

confidence: 99%

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Application of the Tikhonov Regularization Technique to the Equivalent Magnetic Currents Near-Field Technique

Colinas

Goussard

Laurin

2004

IEEE Trans. Antennas Propagat.

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The equivalent magnetic currents method can be used to characterize radiating structures and to obtain information about the current distribution on the radiating device under test (DUT). In order to do so, the system is assumed to be linear and inversion from near-field measurements can be carried out using numerical techniques such as the singular value decomposition. However this approach is very sensitive to modeling and measurement errors, which is a consequence of the ill-conditioned nature of the inversion process. Here, we propose to account for the ill-conditioning by using a Tikhonov regularization technique to perform the inversion. This technique requires a regularization parameter to be set to an appropriate value, and we show that a generalized cross-validation approach yields adequate determination of the regularization parameter directly from the measured data. The proposed method can be tailored to account for specific characteristics of the DUT. This point is illustrated by the estimation of the current distribution of a bidimensional radiating structure for which prior information about the orientation of radiating edges is incorporated into the inversion method.Index Terms-Antenna measurements, equivalent magnetic currents (EqMC), generalized cross validation, ill-posed problems, inverse problems, near field (NF), Tikhonov regularization technique (TRT).

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Section: Generalized Cross Validation For Estimation Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of the Tikhonov Regularization Technique to the Equivalent Magnetic Currents Near-Field Technique

Colinas

Goussard

Laurin

2004

IEEE Trans. Antennas Propagat.

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show abstract

“…These polynomials will be henceforth denoted as H( s) 1 . As seen from (1), (2), the polynomial H( s), can be written as follows:…”

Section: Antenna Array Diagnostics From Linear and Non-linear Measurementioning

confidence: 99%

“…For the linear (field measurements) case, std. (e.g., Gauss-Seidel [3]) methods would be plagued by ill-conditioning especially as the distance between the source and the measurement plane is increased [1]. For the nonlinear (intensity measurements) case, naive conjugate-gradient (henceforth CG) minimization algorithms would be prone to trapping by local minima, in view of the non-convex character of the problem [2].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Faulty Element Diagnostics of Large Antenna Arrays by Discrete Mean Field Neural Nets

Castaldi¹,

Pierro²,

Pinto³

2000

PIER

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A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

Xiong

Xiao

2020

IEEE Access

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A diagnosing method for phased antenna array element failures is proposed. The element excitation amplitudes and phases are reconstructed by a compressed sensing based approach, in which the radiated electric fields of the array are sampled by a single fixed receiving antenna. The diagnosing can be processed when the phased array is still in service. Particularly, it can be specialized for detecting faults only. Element excitation phases are designed to follow Bernoulli distribution, which is difficult to be realized in conventional geometric sampling methods. It is capable to provide effective and simultaneous detection for different types of failures with phase control means that are simpler comparing with other methods in which excitation phase adjustment is required. Especially, a two-step detection strategy is proposed to effectively detect phase failures due to faultily short-circuited phase shifters. Numerical results illustrate the effective sensing range of a single receiving antenna. Full-wave simulations validate the diagnosing performance in the presence of mutual couplings between array elements.

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Regularized matrix method for near-field diagnostic techniques of phased array antennas

Cited by 6 publications

References 8 publications

Application of the Tikhonov Regularization Technique to the Equivalent Magnetic Currents Near-Field Technique

Application of the Tikhonov Regularization Technique to the Equivalent Magnetic Currents Near-Field Technique

Efficient Faulty Element Diagnostics of Large Antenna Arrays by Discrete Mean Field Neural Nets

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

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