Multi-Source DoA Estimation of EM Waves Impinging Spherical Antenna Array With Unknown Mutual Coupling Using Relative Signal Pressure Based Multiple Signal Classification Approach

Abstract

Spherical antenna array (SAA) is a configuration that scans almost all the radiation sphere with constant directivity. It finds applications in spacecraft and satellite communication. Multiple signal classification (MUSIC) is a widely used multiple source direction-of-arrival (DoA) estimation method because of its low complexity implementation in practical applications. Conversely, it is susceptible to noise, which consequently affects its accuracy of localization. In this paper, MUSIC-based methods that operate at low signal-to-noise ratio (SNR) are developed via relative electromagnetic (EM) wave pressure measurements of a SAA. The proposed methods are the relative pressure MUSIC (RP-MUSIC), and in spherical domain (SH-RP-MUSIC). The developed SH-RP-MUSIC algorithm is in spherical domain thereby allows frequency-smoothing approach for the de-correlation of the coherent source signals towards an enhanced accuracy of localization. Both RP-MUSIC and SH-RP-MUSIC algorithms developed have the ability to estimate the number of active sources that is a priori knowledge of the conventional MUSIC algorithm. Numerical experiments were used to demonstrate the adequacy of the developed algorithms. In addition, measured data from experiment, which is the practically acceptable way to examine any procedure is employed to demonstrate the merits of the developed algorithms against the conventional MUSIC algorithm and other recent multiple source localization method in literature. Finally, in order to achieve DoA estimations with adequate localization accuracy at low SNR using SAA, SH-RP-MUSIC algorithm is a better choice.

A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array with Undefined Mutual Coupling

“…The source s is detected using SAA with radius 𝑟 𝑎 and M number of elements. The EM wave pressure at 𝒓 = (𝑟, 𝜃, 𝜙) on the SAA is expressed as [1], [23]…”

“…The Estimation of direction-of-arrival (DoA) is an important and crucial topic in different electromagnetic (EM) related research areas. It finds applications in wireless communications, radar, sonar, and telecommunication [1]- [8]. When the DoAs of a receive mode EM waves is known, the localization of the corresponding sources is effectively possible.…”

Random Convolutional Kernels for Space-Detector Based Gravitational Wave Signals

“…Recent developments in machine learning, most notably in neural networks, have improved signal detection performance, making it possible to extract and detect complex signals more quickly and easily [10][11][12][13][14][15]. Eventually, these methods found their application in gravitational wave detection too; some early works utilize convolutional neural networks and achieve competent accuracy and order of magnitude faster inference time when compared to matched filtering [16,17].…”

“…Performance analysis of Minirocket for ground-based signal-to-noise ratios(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) signals.…”

Subspace Pseudointensity Vectors Approach for DoA Estimation Using Spherical Antenna Array in the Presence of Unknown Mutual Coupling

“…Different DoA estimation approaches for use in the SH domain have been reported in the literature [3][4][5][6][8][9][10][11][12][13][14][15][16][17]. Some of the most popular approaches include the multiple signal classification (MUSIC) approach [3], estimation of signal parameters through rotational invariance technique (ESPRIT) technique [5][6][7][8][9], beamforming, and the maximum likelihood (ML) methods [4,15].…”