Spherical Wave Model Research Articles

Short-Range MIMO Throughput Prediction Based on Spherical Wave Model

Short-Range MIMO Throughput Prediction Based on Spherical Wave Model

Fluctuations of polyspectra in spherical and Euclidean random wave models

Fluctuations of polyspectra in spherical and Euclidean random wave models

Low-complex channel estimation in extra-large scale MIMO with the spherical wave properties

This paper investigates the low-complex linear minimum mean squared error (LMMSE) channel estimation in an extra-large scale MIMO system with the spherical wave model (SWM). We model the extra-large scale MIMO channels using the SWM in the terahertz (THz) line-of-sight propagation, in which the transceiver is a uniform circular antenna array. On this basis, for the known channel covariance matrix (CCM), a low-complex LMMSE channel estimation algorithm is proposed by exploiting the spherical wave properties (SWP). Meanwhile, for the unknown CCM, a similar low-complex LMMSE channel estimation algorithm is also proposed. Both theoretical and simulation results show that the proposed algorithm has lower complexity without reducing the accuracy of channel estimation.

DRFM Repeater Jamming Suppression Method Based on Joint Range-Angle Sparse Recovery and Beamforming for Distributed Array Radar

Distributed array radar achieves high angular resolution and measurement accuracy, which could provide a solution to suppress digital radio frequency memory (DRFM) repeater jamming. However, owing to the large aperture of a distributed radar, the far-field plane wave assumption is no longer satisfied. Consequently, traditional adaptive beamforming methods cannot work effectively due to mismatched steering vectors. To address this issue, a DRFM repeater jamming suppression method based on joint range-angle sparse recovery and beamforming for distributed array radar is proposed in this paper. First, the steering vectors of the distributed array are reconstructed according to the spherical wave model under near-field conditions. Then, a joint range-angle sparse dictionary is generated using reconstructed steering vectors, and the range-angle position of jamming is estimated using the weighted L1-norm singular value decomposition (W-L1-SVD) algorithm. Finally, beamforming with joint range-angle nulling is implemented based on the linear constrained minimum variance (LCMV) algorithm for jamming suppression. The performance and effectiveness of proposed method is validated by simulations and experiments on an actual ground-based distributed array radar system.

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

To improve the computation and real-time performances of the multiple signal classification (MUSIC) algorithm in 3D space, a fast sound source localization method based on the bat algorithm (BA) and the 3D-MUSIC, called BA-based 3D-MUSIC algorithm (3D-BMUSIC), is presented in this paper. 3D-BMUSIC greatly reduces the computation load by replacing the regular grid search with the BA. First, the near-field spherical wave model is established to obtain the spectral function of the 3D-MUSIC. Then, the spectral function is defined as the fitness function, which calculates the fitness value corresponding to each bat position. Finally, the global optimal bat position with the largest fitness value, as sound source localization, is obtained by successive iteration and sorting. The simulation and experiment show that 3D-BMUSIC accurately estimates the DOA and distance of near-field sources, and the root-mean-square error (RMSE) of 3D-BMUSIC is less than that of 3D-MUSIC. In addition, 3D-BMUSIC effectively reduces the computation time by approximately 96–98%. With shorter computation time and higher efficiency, 3D-BMUSIC promotes hardware implementation and is more suitable for high-precision localization of near-field sound sources.

Spectral Element Modeling of Acoustic to Seismic Coupling Over Topography

AbstractAcoustic waves in the atmosphere are commonly recorded on seismometers as they couple into the ground. These signals, here called ground coupled airwaves, are not commonly considered in numerical modeling of infrasound propagation, which often assumes a rigid unmeshed boundary. Starting from an analytically‐tractable spherical wave model, we analyze how the coupling of an acoustic wave into a planar elastic halfspace changes over a wide range of scenarios. We use energy admittance to quantify acoustic to seismic coupling over both a planar elastic halfspace and meshed topography. Our spectral element and analytic calculations have different maxima as a function of incidence angle, with very high admittance values for near‐vertical incidence (maximum ≈78%). Energy admittance calculations at shallow incidence angles are much smaller (less than 1%). In simulations over the complex topography of Sakurajima Volcano, we attribute the variable spatial pattern of energy admittance to changes in earth parameters between each model. The observed pressure difference over the simulated 15 km region appears to be . While this value is relatively small, the cumulative addition over 100s of km and multiple acoustic bounce points may be significant. Acoustic to seismic coupling along the propagation path may bias long distance yield estimates, particularly when infrasound propagates over regions with steep topography or particularly slow seismic velocities, such as alluvial planes.

Complex ResNet Aided DoA Estimation for Near-Field MIMO Systems

The near-field effect of short-range multiple-input multiple-output (MIMO) systems imposes many challenges on direction-of-arrival (DoA) estimation. Most conventional scenarios assume that the far-field planar wavefronts hold. In this paper, we investigate the DoA estimation problem in short-range MIMO communications, where the effect of near-field spherical wave is non-negligible. By converting it into a regression task, a novel DoA estimation framework based on complex-valued deep learning (CVDL) is proposed for the near-field region in short-range MIMO communication systems. Under the assumption of a spherical wave model, the array steering vector is determined by both the distance and the direction. However, solving this regression task containing a massive number of variables is challenging, since datasets need to capture numerous complicated feature representations. To overcome this, a virtual covariance matrix (VCM) based on received signals is constructed, and thus such features extracted from the VCM can deal with the complicated coupling relationship between the direction and the distance. Although the emergence of wireless big data driven by future communication networks promotes deep learning-based wireless signal processing, the learning algorithms of complex-valued signals are still ongoing. This paper proposes a one-dimensional (1-D) residual network that can directly tackle complex-valued features due to the inherent 1-D structure of signal subspace vectors. In addition, we put forth a cropped VCM based policy which can be applied to different antenna sizes. The proposed method is able to fully exploit the complex-valued information. Our simulation results demonstrate the superiority of the proposed CVDL approach over the baseline schemes in terms of the accuracy of DoA estimation.

Performance comparison of acoustic emission sensor arrays in different topologies for the localization of gas leakage on a flat-surface structure

The topology of the acoustic emission sensor array has an important effect on the performance of the leak localization technique. This paper compares the performances of different topologies of acoustic emission sensor arrays in the localization of gas leakage on a flat-surface structure. The principle of the leak localization is based on the near-field beamforming according to the spherical wave model and the narrowband filtering which can effectively avoid the influence of acoustic dispersion. The effect of different arrangements of the sensing elements in a sensor array on the localization accuracy is investigated and discussed. Eight typical topologies, including line, L-shaped, cross, triangle, star, circular, semi-circular and square shapes, are appraised through computer simulation. Simulation results suggest that all the arrays can perform leak localization but with different accuracies and that the L-shaped array outperforms all other topologies under the similar conditions. Furthermore, the optimal number of sensors in the L-shaped array which can maintain a reasonable accuracy of localization is analyzed. Experimental work was carried out on a laboratory scale test rig to verify and assess the effectiveness of the L-shaped array. The simulation and experimental results demonstrate that the L-shaped array is capable of identifying the location of a leak hole on a plate with a reasonably good accuracy.

Gaussian beam scintillation index for slant path in weak turbulence: closed form expressions

The scintillation index (SI) is an important issue in studying the effect of the atmospheric turbulence in the light waves. With the Rytov weak fluctuation theory, the SI is commonly referred to the Rytov parameter. The previous studies dealt with the plane wave and spherical wave models. Each of these gives an idea of how an optical beam will react to turbulence but are not realistic. One is infinitely long, while the other is an infinitesimal point source. The Gaussian beam wave is the most realistic of the optical waves, but also the most complex to use for calculations. In this paper, a closed form expression for Gaussian beam SI propagation in slant path and through weak fluctuation is derived using the polynomial model of the refractive index structure parameter. The slant path SI model of the plane and spherical waves can be generated from the SI expression of Gaussian beam. The analytic expressions are obtained and are then used to analyze the effect of propagation distance, transmitter/receiver heights, and elevation angle on the SI. Signal to noise ratio and bit error rate are calculated for performance evaluation showing a significant enhancement at elevation angles greater than 45°.

Multichannel Phase Calibration for Linear Array Based on Extended <inline-formula> <tex-math notation="LaTeX">$\omega K$</tex-math> </inline-formula> Algorithm and Minimum-Entropy Method

Millimeter-wave imaging techniques have been used for security inspection at important checkpoints. With the increase of working frequencies of the imaging systems, the precise multichannel phase calibration becomes more and more important. Most of the traditional algorithms are used for the calibration of passive receiving antenna array, based on the signal model of far-field plane wave. However, the near-field spherical wave model should be utilized for the active wideband near-field imaging applications. Consequently, the traditional calibration algorithms cannot be used in wideband near-field imaging systems. The metal plate is usually employed for the calibration of wideband near-field imaging systems, but the precision is very sensitive to the flatness of the surface of the metal plate, which will result in additional phase error after calibration. In this letter, a multichannel phase error estimation and calibration method is proposed for the wideband linear array system. By using an extended $\omega K$ algorithm and the minimum-entropy method, the additional phase error of each channel after preliminary calibration is estimated and calibrated. Simulations and experimental results show the effectiveness of the proposed method.

Channel Characterization for Wideband Large-Scale Antenna Systems Based on a Low-Complexity Maximum Likelihood Estimator

Wideband large-scale array systems operating at millimeter-wave bands are expected to play a key role in future communication systems. It is recommended by standardization groups to use spherical-wave models (SWMs) to characterize the channel in near-field cases because of the large array apertures and the small cell size. However, this feature is not widely reflected in channel models yet, mainly due to the high computational complexity of SWMs compared to that of the conventional plane-wave model (PWM), especially when ultrawideband signals are considered. In this paper, a maximum likelihood estimator of low computational complexity is implemented with an SWM for ultrawideband signals. The measurement data obtained from an ultrawideband large-scale antenna array system at 28–30 GHz are processed with the proposed algorithm. The power azimuth-delay profiles estimated from the SWM and the PWM are compared to those obtained from rotational horn antenna measurement, respectively. It shows that the multipath components (MPCs) are well-estimated with the proposed algorithm, and significant improvement in estimation performance is achieved with the SWM compared to the PWM. Moreover, the physical interpretation of the estimated MPCs is also given along with the estimated scatterers.

Validation with measurements of plane and spherical-wave UTD-PO propagation models which assume flat-topped obstacles

Two radiowave propagation models which calculate the multiple-building diffraction losses through the corresponding Uniform Theory of Diffraction-Physical Optics (UTD-PO) formulations are validated with measurements performed in different locations of an urban environment. The main advantage of such solutions is that, since they are recursive, the calculations are expressed in terms of single diffractions (high-order diffraction terms are not considered in the diffraction coefficients), thus showing better computational efficiency than other existing methods. Buildings are modeled as flat-topped obstacles and one formulation assumes plane-wave incidence over the obstacles while the other considers a spherical wave impinging over the array of rooftops. The locations in which the spherical-wave model should be used instead of the plane-wave method in order to obtain more realistic results are discussed.

Analysis of Panel Antenna Arrays in Los MIMO System

In this paper, we investigate the design of multiple panel arrays (MPAs) in line of sight (LoS) multiple-input-multiple-output (MIMO) communication systems. We utilize the spherical-wave model for the LoS channel component. The fundamental relations among key design parameters in MPAs LoS MIMO system are studied to obtain the maximum spatial multiplexing gain according to the effective degrees of freedom and channel capacity. We further analyze the performance of MPAs system when the array size and transmission distance are not matched and propose an algorithm to optimize the location of antennas. Numerical results indicate that the proposed algorithm can reduce the computational load compared with the exhaustive approach for the similar system performance. Moreover, the optimized panel antenna array is robust to the geometrical change, misplacement, and signal-to-noise-ratio.

Transmit Design for Short-Range MIMO Channels With the Spherical-Wave Model

In this letter, we investigate the transmit design for short-range multiple-input multiple-output (MIMO) channels with the spherical-wave model (SWM) in three-dimensional (3D) space. We first establish the antenna array with arbitrary orientations in 3D space. On this basis, we propose a practical and low-complexity transmit scheme with the SWM in short-range MIMO channels. The analytical expressions for the transmit directions and the power allocation of the proposed transmit scheme is also derived. Both the analytical and simulation results show that the proposed scheme can obtain performance improvement compared with the equal power transmission.

Channel capacity investigation of a linear massive MIMO system using spherical wave model in LOS scenarios

Massive multiple-input multiple-output (MIMO) is a key technology for the 5th generation (5G) of wireless communication systems. The traditional plane wave channel model (PWM) is often not suitable for the large antenna structure, and in certain cases should be replaced by the more accurate spherical wave model (SWM). By using the spherical wave characterization method, this paper investigates the channel capacity performance of a linear massive MIMO system in line-of-sight (LOS) scenarios. Two types of access settings, the point to point (PTP) system and multi-user (MU) system, are considered. In the PTP setting, a geometrical optimization is performed to obtain configurations that are able to generate a full rank channel matrix for a linear massive MIMO system, which yields full spatial diversity even in LOS scenarios. Compared with the approximate and commonly applied rank-1 PWM, this is very useful for fixed wireless access and radio relay systems requiring high throughput. For the MU case, we compare the eigenvalue distributions of the LOS channels using the plane wave and spherical wave characterization method, and sum rate results are obtained by Monte Carlo simulations. The results show that MU systems using the more realistic and accurate SWM can achieve a higher sum rate than results from the PWM. This is beneficial and informative when designing massive MIMO wireless networks.

Effects of Array Orientations on Degrees of Freedom for 3D LoS Channels in Short-Range Communications

In this letter, we investigate the spatial degrees of freedom (DoF) of line-of-sight (LoS) channels in three-dimensional (3D) space with respect to the array orientations in short-range communications. First, the corresponding response of LoS channels is modeled using the spherical-wave model (SWM). The analytical expression for the spatial DoF of LoS channels with various array orientations is then derived and compared with that obtained in long-range communications. Both the analytical and simulation results show that the array orientations have a significant impact on the spatial DoF of short-range LoS channels.

Analysis of the Capacity Statistics for 2 <inline-formula> <tex-math notation="TeX">$\times$</tex-math></inline-formula> 2 3D MIMO Channels in Short-Range Communications

In this letter, we investigate the capacity of 2 × 2 short-range line-of-sight (LOS) multiple-input multiple-output (MIMO) channels in three-dimensional (3D) space. The corresponding channel with arbitrary antenna orientations in 3D space is modeled using the spherical-wave model (SWM) , based on which the capacity without channel knowledge at the transmitter is obtained. The exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF) , and expectation of the capacity are then derived and compared with those obtained by the plane-wave model (PWM) . Both the analytical and simulation results show that the capacity is determined by a factor depending on the transceiver distance, the wavelength, and the array size.

Optimal 2x2 Antenna Placement for Short-Range Communications

In this letter, we investigate the optimal antenna placement with path loss and phase differences in terms of the condition number in short-range communications. First, the line-of-sight (LOS) 2×2 multiple-input multiple-output (MIMO) channel matrix with path loss and phase differences is modeled using the spherical-wave model. We then derive the explicit analytical expression and the geometrical pattern for the optimal antenna placement when considering the joint effects of path loss and phase differences, which are compared with the analytical expression and the geometrical pattern when considering only the phase differences. By the optimal antenna placement, the high correlation between the LOS responses can be overcome. Analytical and numerical results show that the path loss differences for short-range communications have a significant impact on the condition number.

Particle velocity estimation based on a two-microphone array and Kalman filter

A traditional method to measure particle velocity is based on the finite difference (FD) approximation of pressure gradient by using a pair of well matched pressure microphones. This approach is known to be sensitive to sensor noise and mismatch. Recently, a double hot-wire sensor termed Microflown became available in light of micro-electro-mechanical system technology. This sensor eliminates the robustness issue of the conventional FD-based methods. In this paper, an alternative two-microphone approach termed the u-sensor is developed from the perspective of robust adaptive filtering. With two ordinary microphones, the proposed u-sensor does not require novel fabrication technology. In the method, plane wave and spherical wave models are employed in the formulation of a Kalman filter with process and measurement noise taken into account. Both numerical and experimental investigations were undertaken to validate the proposed u-sensor technique. The results have shown that the proposed approach attained better performance than the FD method, and comparable performance to a Microflown sensor.

An Acoustic Localization System Using Microphone Array for Mobile Robot

Robot audition system can greatly improve the adaptability of mobile robots especially in the case of robot vision system can't work effectively. So an acoustic localization system using microphone array for mobile robot is proposed in this paper. In order to localize the sound source target, the microphone array used in the system consists of four microphones which were placed respectively on the vertexes of regular tetrahedron because of sound's omni-directional property. According to the plane wave model of sound's propagation and the spherical wave model of sound's propagation, two different localization algorithms based on time delay of arrival are developed in this paper. The hardware and software of the experiment platform are also introduced in this paper. The experimental results show that the acoustic localization system can make the mobile robot rapidly and accurately reach the location of the sound source target.