scholarly journals 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 ◽  
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.

scholarly journals Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 136
Author(s):  
Pan Gong ◽  
Xixin Chen
Keyword(s):  
Covariance Matrix ◽  
Lower Boundary ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Signal Classification ◽  
Computationally Efficient ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Multiple Signal

In this paper, we investigate the problem of direction-of-arrival (DOA) estimation for massive multi-input multi-output (MIMO) radar, and propose a total array-based multiple signals classification (TA-MUSIC) algorithm for two-dimensional direction-of-arrival (DOA) estimation with a coprime cubic array (CCA). Unlike the conventional multiple signal classification (MUSIC) algorithm, the TA-MUSIC algorithm employs not only the auto-covariance matrix but also the mutual covariance matrix by stacking the received signals of two sub cubic arrays so that full degrees of freedom (DOFs) can be utilized. We verified that the phase ambiguity problem can be eliminated by employing the coprime property. Moreover, to achieve lower complexity, we explored the estimation of signal parameters via the rotational invariance technique (ESPRIT)-based multiple signal classification (E-MUSIC) algorithm, which uses a successive scheme to be computationally efficient. The Cramer–Rao bound (CRB) was taken as a theoretical benchmark for the lower boundary of the unbiased estimate. Finally, numerical simulations were conducted in order to demonstrate the effectiveness and superiority of the proposed algorithms.

Direction of Arrival Estimation with Compact Array Antennas

2009 ◽  
pp. 201-216
Author(s):  
Eddy Taillefer ◽  
Jun Cheng ◽  
Takashi Ohira
Keyword(s):  
Single Port ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal Classification ◽  
Direction Of Arrival Estimation ◽  
Multiple Signal Classification ◽  
Array Antennas ◽  
Power Pattern ◽  
Parasitic Array ◽  
Compact Array

This chapter presents direction of arrival (DoA) estimation with a compact array antenna using methods based on reactance switching. The compact array is the single-port electronically steerable parasitic array radiator (Espar) antenna. The antenna beam pattern is controlled though parasitic elements loaded with reactances. DoA estimation using an Espar antenna is proposed with the power pattern cross correlation (PPCC), reactance-domain (RD) multiple signal classification (MUSIC), and, RD estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. The three methods exploit the reactance diversity provided by an Espar antenna to correlate different antenna output signals measured at different times and for different reactance values. The authors hope that this chapter allows the researchers to appreciate the issues that may be encountered in the implementation of direction-finding application with a single-port compact array like the Espar antenna.

scholarly journals Source Localization of EM Waves in the Near-Field of Spherical Antenna Array in the Presence of Unknown Mutual Coupling

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Oluwole John Famoriji ◽  
Thokozani Shongwe
Keyword(s):  
Antenna Array ◽  
Source Localization ◽  
Antenna Arrays ◽  
Mutual Coupling ◽  
Near Field ◽  
Ground Truth ◽  
Doa Estimation ◽  
Measured Data ◽  
Practical Applications ◽  
Spherical Antenna

To obtain an antenna array with isotropic radiation, spherical antenna array (SAA) is the right array configuration. The challenges of locating signals transmitted within the proximity of antenna array have been investigated considerably in the literature. However, near-field (NF) source localization of signals has hitherto not been investigated effectively using SAA in the presence of mutual coupling (MC). MC is another critical problem in antenna arrays. This paper presents an NF range and direction-of-arrival (DoA) estimation technique via the direction-independent and signal invariant spherical harmonics (SH) characteristics in the presence of mutual coupling. The energy of electromagnetic (EM) signal on the surface of SAA is captured successfully using a proposed pressure interpolation approach. The DoA estimation within the NF region is then calculated via the distribution of pressure. The direction-independent and signal invariant characteristics, which are SH features, are obtained using the DoA estimates in the NF region. We equally proposed a learning scheme that uses the source activity detection and convolutional neural network (CNN) to estimate the range of the NF source via the direction-independent and signal invariant features. Considering the MC problem and using the DoA estimates, an accurate spectrum peak in the multipath situation in conjunction with MC and a sharper spectrum peak from a unique MC structure and smoothing algorithms are obtained. For ground truth performance evaluation of the SH features within the context of NF localization, a numerical experiment is conducted and measured data were used for analysis to incorporate the MC and consequently computed the root mean square error (RMSE) of the source range and NF DoA estimate. The results obtained from numerical experiments and measured data indicate the validity and effectiveness of the proposed approach. In addition, these results are motivating enough for the deployment of the proposed method in practical applications.

A Dynamic Sub-Array Divided Technique for Spherical Conformal Array Antenna Using K-Means Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 2884-2888 ◽  
Author(s):  
Jin Yan Tang ◽  
Yue Lei Xie ◽  
Cheng Cheng Peng
Keyword(s):  
Direction Of Arrival ◽  
Array Antenna ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Conformal Array ◽  
Multiple Signal

In this paper, a sub-array divided technique using K-means algorithm for spherical conformal array is proposed. All elements of spherical conformal array can be divided into a few sub-arrays by employing the K-means algorithm, and the standard multiple signal classification (MUSIC) algorithm is applied to estimate signals Direction-of-arrival (DOA) on these sub-arrays. Simulations of estimating DOA on a rotational spherical conformal array have been made and the results show that the resolution of DOA is improved by our method compare to existing methods.

Study of High Resolution DOA Estimation Based on Vector-Hydrophone

2014 ◽  
Vol 926-930 ◽  
pp. 1795-1799
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo
Keyword(s):  
Doa Estimation ◽  
Spatial Spectrum ◽  
Classification Algorithm ◽  
Signal Classification ◽  
Two Dimensional ◽  
Multiple Signal Classification ◽  
Variance Matrix ◽  
Multiple Signal ◽  
Vector Hydrophone ◽  
Eigen Decomposition

Vector-hydrophone can simultaneously measure acoustic pressure and orthogonal components of the particle velocity. The 180o ambiguity in DOA estimation can be eliminated using information obtained by vector hydrophone array. Multiple signal classification algorithm is a method that takes the eigen-decomposition of data co-variance matrix to obtain the estimation of signal spatial spectrum. The two-dimensional DOA of acoustic sources is estimated based on multiple signal classification algorithm using the vector-hydrophone uniform linear array. Simulation results show that better DOA resolution performance can be obtained from vector hydrophones. Furthermore, the paper takes the de-correlation of correlated sources using spatial smoothness technology to obtain perfect performance of two-dimensional DOA estimation.

MULTIPLE SIGNAL CLASSIFICATION FOR GRAVITATIONAL WAVE BURST SEARCH

2013 ◽  
Vol 23 ◽  
pp. 74-81
Author(s):  
JUNWEI CAO ◽  
ZHENGQI HE
Keyword(s):  
Gravitational Wave ◽  
Doa Estimation ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Wave Characteristics ◽  
Multiple Signal ◽  
Promising Tool ◽  
Arbitrary Position ◽  
Noise Covariance

This work is mainly focused on the application of the multiple signal classification (MUSIC) algorithm for gravitational wave burst search. This algorithm extracts important gravitational wave characteristics from signals coming from detectors with arbitrary position, orientation and noise covariance. In this paper, the MUSIC algorithm is described in detail along with the necessary adjustments required for gravitational wave burst search. The algorithm's performance is measured using simulated signals and noise. MUSIC is compared with the Q-transform for signal triggering and with Bayesian analysis for direction of arrival (DOA) estimation, using the Ω-pipeline. Experimental results show that MUSIC has a lower resolution but is faster. MUSIC is a promising tool for real-time gravitational wave search for multi-messenger astronomy.

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