DoA Estimation Using Neural Tangent Kernel under Electromagnetic Mutual Coupling

Antenna element mutual coupling degrades the performance of Direction of Arrival (DoA) estimation significantly. In this paper, a novel machine learning-based method via Neural Tangent Kernel (NTK) is employed to address the DoA estimation problem under the effect of electromagnetic mutual coupling. NTK originates from Deep Neural Network (DNN) considerations, based on the limiting case of an infinite number of neurons in each layer, which ultimately leads to very efficient estimators. With the help of the Polynomial Root Finding (PRF) technique, an advanced method, NTK-PRF, is proposed. The method adapts well to multiple-signal scenarios when sources are far apart. Numerical simulations are carried out to demonstrate that this NTK-PRF approach can handle, accurately and very efficiently, multiple-signal DoA estimation problems with realistic mutual coupling.

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DOA Estimation of Noncircular Signals for Coprime Linear Array via Polynomial Root-Finding Technique

Journal of Circuits System and Computers ◽

10.1142/s0218126621500286 ◽

2020 ◽

pp. 2150028

Author(s):

Hui Zhai ◽

Zheng Li ◽

Xiaofei Zhang

Keyword(s):

Linear Array ◽

Doa Estimation ◽

Music Algorithm ◽

Uniform Linear Array ◽

Estimation Algorithms ◽

Root Finding ◽

Noncircular Signals ◽

Peak Search ◽

Simulation Results ◽

Polynomial Root Finding

In this paper, we investigate the direction of arrival (DOA) estimation problem of noncircular signals for coprime linear array (CLA). From the perspective of the CLA as extracted from a filled uniform linear array (ULA), a noncircular root-MUSIC algorithm is proposed to estimate the DOA which can avoid the spectral peak search and lower the computational complexity. Due to the noncircular characteristic, the proposed algorithm enables to resolve more sources than sensors. Meanwhile, the proposed algorithm has better angle estimation performance than some conventional DOA estimation algorithms. Numerical simulation results illustrate the performance of the proposed method.

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Multiple Signal DoA Estimation with Unknown Electromagnetic Coupling using Gaussian Process

2020 IEEE Asia-Pacific Microwave Conference (APMC) ◽

10.1109/apmc47863.2020.9331546 ◽

2020 ◽

Author(s):

Qifeng Wang ◽

Nicholas E. Buris ◽

Xiaolin Hu

Keyword(s):

Gaussian Process ◽

Electromagnetic Coupling ◽

Doa Estimation ◽

Multiple Signal ◽

Signal Doa Estimation

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Direction-of-Arrival Estimation of Electromagnetic Wave Impinging on Spherical Antenna Array in the Presence of Mutual Coupling Using a Multiple Signal Classification Method

Electronics ◽

10.3390/electronics10212651 ◽

2021 ◽

Vol 10 (21) ◽

pp. 2651

Author(s):

Oluwole John Famoriji ◽

Thokozani Shongwe

Keyword(s):

Electromagnetic Wave ◽

Fourier Series ◽

Antenna Array ◽

Mutual Coupling ◽

Direction Of Arrival ◽

Doa Estimation ◽

Signal Classification ◽

Multiple Signal Classification ◽

Multiple Signal ◽

Spherical Antenna

A spherical antenna array (SAA) is the configuration of choice in obtaining an antenna array with isotropic characteristics. An SAA has the capacity to receive an electromagnetic wave (EM) with equal intensity irrespective of the direction-of-arrival (DoA) and polarization. Therefore, the DoA estimation of electromagnetic (EM) waves impinging on an SAA with unknown mutual coupling needs to be considered. In the spherical domain, the traditional multiple signal classification algorithm (SH-MUSIC) is faced with a computational complexity problem. This paper presents a one-dimensional MUSIC method (1D-MUSIC) for the estimation of the azimuth and elevation angles. An intermediate mapping matrix that exists between Fourier series and the spherical harmonic function is designed, and the Fourier series Vandermonde structure is used for the realization of the polynomial rooting technique. This mapping matrix can be computed prior to the DoA estimation, and it is only a function of the array configuration. Based on the mapping matrix, the 2-D angle search is transformed into two 1-D angle findings. Employing the features of the Fourier series, two root polynomials are designed for the estimation of the elevation and azimuth angles, spontaneously. The developed method avoids the 2-D spectral search, and angles are paired in automation. Both numerical simulation results, and results from experimental measured data (i.e., with mutual coupling effect incorporated), show the validity, potency, and potential practical application of the developed algorithm.

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Multiple Signal Direction of Arrival (DoA) Estimation for a Switched-beam System Using Neural Networks

PIERS Online ◽

10.2529/piers070215034532 ◽

2007 ◽

Vol 3 (8) ◽

pp. 1160-1164 ◽

Cited By ~ 5

Author(s):

Konstantinos A. Gotsis ◽

E. G. Vaitsopoulos ◽

Katherine Siakavara ◽

J. N. Sahalos

Keyword(s):

Neural Networks ◽

Direction Of Arrival ◽

Doa Estimation ◽

Multiple Signal ◽

Beam System

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DOA estimation of coherently distributed sources in massive MIMO systems with unknown mutual coupling

Digital Signal Processing ◽

10.1016/j.dsp.2021.102987 ◽

2021 ◽

Vol 111 ◽

pp. 102987

Author(s):

Ye Tian ◽

Yunbai Qin ◽

Zhiyan Dong ◽

He Xu

Keyword(s):

Massive Mimo ◽

Mutual Coupling ◽

Mimo Systems ◽

Doa Estimation

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A printed multiband MIMO antenna with decoupling element

International Journal of Microwave and Wireless Technologies ◽

10.1017/s1759078719000096 ◽

2019 ◽

Vol 11 (4) ◽

pp. 413-419 ◽

Cited By ~ 1

Author(s):

Ziyu Xu ◽

Qisheng Zhang ◽

Linyan Guo

Keyword(s):

Mutual Coupling ◽

Surface Current ◽

Antenna System ◽

Antenna Element ◽

Coupling Mechanism ◽

Mimo Antenna ◽

Resonant Modes ◽

Monopole Antennas ◽

Input Multiple Output ◽

Ground Plate

AbstractA printed multiband Multi-Input Multiple-Output (MIMO) antenna is proposed in this paper. This MIMO antenna system comprises two symmetric printed monopole antennas. Each antenna element consists of multiple bend lines, producing four resonant modes and covering the GSM900, PCS, LTE2300, and 5G bands. Simulated and measured results prove that the proposed MIMO antenna can be applied to traditional 2G, 3G, 4G, and present 5G mobile communication. By etching four inverted L-shaped grooves on its ground plate, mutual coupling between the adjacent antenna elements has been suppressed. This makes the |S21| at all four resonant modes is lower than −40 dB. In addition, its low coupling mechanism has been analyzed by surface current distribution. The designed multiband MIMO antenna provides an idea of reference to realize low mutual coupling between antenna elements, which is also realizable in infrared or optical regimes with appropriate designs.

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Polynomial root finding and polynomiography, by Bahman Kalantari

Journal of Mathematics and the Arts ◽

10.1080/17513472.2011.557567 ◽

2011 ◽

Vol 5 (1) ◽

pp. 48-49

Author(s):

Gary Greenfield

Keyword(s):

Root Finding ◽

Polynomial Root Finding

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Thermos Array: Two-Dimensional Sparse Array with Reduced Mutual Coupling

International Journal of Antennas and Propagation ◽

10.1155/2018/3624514 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Lei Sun ◽

Minglei Yang ◽

Baixiao Chen

Keyword(s):

Closed Form ◽

Degrees Of Freedom ◽

Mutual Coupling ◽

Doa Estimation ◽

Two Dimensional ◽

Spatial Smoothing ◽

Planar Arrays ◽

Half Wavelength ◽

Planar Array ◽

Small Spacing

Sparse planar arrays, such as the billboard array, the open box array, and the two-dimensional nested array, have drawn lots of interest owing to their ability of two-dimensional angle estimation. Unfortunately, these arrays often suffer from mutual-coupling problems due to the large number of sensor pairs with small spacing d (usually equal to a half wavelength), which will degrade the performance of direction of arrival (DOA) estimation. Recently, the two-dimensional half-open box array and the hourglass array are proposed to reduce the mutual coupling. But both of them still have many sensor pairs with small spacing d, which implies that the reduction of mutual coupling is still limited. In this paper, we propose a new sparse planar array which has fewer number of sensor pairs with small spacing d. It is named as the thermos array because its shape seems like a thermos. Although the resulting difference coarray (DCA) of the thermos array is not hole-free, a large filled rectangular part in the DCA can be facilitated to perform spatial-smoothing-based DOA estimation. Moreover, it enjoys closed-form expressions for the sensor locations and the number of available degrees of freedom. Simulations show that the thermos array can achieve better DOA estimation performance than the hourglass array in the presence of mutual coupling, which indicates that our thermos array is more robust to the mutual-coupling array.

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