Virtual Array Research Articles

Free-field perceptual evaluation of virtual acoustic rendering algorithms using two head-related impulse response delay treatment strategies

Sound scenes can be auralized over headphones using binaural rendering techniques in conjunction with a set of head-related impulse responses (HRIRs). If the directions of the sound objects to be rendered are known, either virtual loudspeaker or Ambisonic scene-based techniques may be used, each of which introduce spatial and timbral artifacts at lower spatial resolutions. Neal and Zahorik quantitatively evaluated the effect of separately applying the HRIR delays to time-aligned HRIRs for use with virtual loudspeaker array techniques, referred to as the prior HRIR delays treatment strategy (J. Acoust. Soc. Am. 2022). The present work aims to perceptually validate their quantitative results in a listening study. Free-field point sources were binaurally rendered using five different methods: vector-based amplitude panning, Ambisonics panning, direct spherical harmonic transform of the HRIR set, MagLS, and Principal Component-Base Amplitude Panning (Neal and Zahorik, Audio Eng. Soc. AVAR Conference 2022). Renderings were simulated at various directions and spatial resolutions, both with and without the prior HRIR delays treatment strategy and compared to direct HRIR convolution. Broadband noise served as a critical test signal for revealing changes in timbre and localization and a high-resolution binaural head HRIR dataset was used. The subjective data analysis will be presented.

Underwater target detection using a pair of omnidirectional transducers in extremely shallow water

In extremely shallow water, such as bays and inlets, active sonar may not work sufficiently well to detect underwater threats owing to multiple reflections and strong reverberations at the sea surface and seafloor. In this study, we developed "gate sonar" on the basis of a unique method of detecting changes in the pulse signal propagated between a pair of omnidirectional transducers in a surveyed area when a target passes between the transducers. To detect changes in the received signal, we employed a time-reversed pulse as the source signal for the gate sonar; this pulse can be created even from a pair of transducers by using a virtual array formed owing to reflections at the surface and bottom boundaries. As a result of experiments in a 25 m-long swimming pool, we confirmed that the gate sonar can recognize the changes in the received signal and functions as designed. Furthermore, by applying convolutional neural network (CNN) to the received signal waveform and its spectrogram as input images, we demonstrated that the proposed time reversal mirror (TRM)-based gate sonar can improve the detection of targets, with the spectrogram performing slightly better.

A Novel Approach for Direction of Arrival Estimation in Co-Located MIMO Radars by Exploiting Extended Array Manifold Vectors.

Multiple-input multiple-output (MIMO) radars enable better estimation accuracy with improved resolution in contrast to traditional radar systems; thus, this field has attracted attention in recent years from researchers, funding agencies, and practitioners. The objective of this work is to estimate the direction of arrival of targets for co-located MIMO radars by proposing a novel approach called flower pollination. This approach is simple in concept, easy to implement and has the capability of solving complex optimization problems. The received data from the far field located targets are initially passed through the matched filter to enhance the signal-to-noise ratio, and then the fitness function is optimized by incorporating the concept of virtual or extended array manifold vectors of the system. The proposed approach outperforms other algorithms mentioned in the literature by utilizing statistical tools for fitness, root mean square error, cumulative distribution function, histograms, and box plots.

Nonorthogonal waveform assisted DOA estimation for joint MIMO sensing and communication

Conventional direction-of-arrival (DOA) estimation methods for multiple-input multiple-output (MIMO) joint sensing and communication system normally pursue high estimation accuracy and resolution by imposing orthogonal waveforms. However, such operation results in a deterioration of communication performance. In this paper, we propose a nonorthogonal waveform assisted DOA estimation algorithm, where an augmented virtual array is derived by exploiting the nonorthogonal MIMO communication waveforms, while a high communication rate can still be maintained. To estimate the round-trip sensing channels of each subcarrier, we utilize the transmitted symbols as pilot symbols, and obtain all the channel coefficients with a minimum mean square error solver. A virtual channel matrix can be formulated with these channel coefficients, which can be regarded as the samples of an augmented virtual array. Based on that, the subspace processing can be conducted for DOA estimation with fully nonorthogonal waveforms. Furthermore, the rank deficiency property of the equivalent signal matrix of the virtual array is analyzed when the distance of targets are identical. To address the problem, a Toeplitz reconstruction method is proposed to restore the rank of the rank-deficient equivalent signal matrix for DOA estimation. Simulations show that the proposed nonorthogonal waveform assisted DOA estimation algorithm outperforms the conventional methods in terms of resolution and accuracy, while maintaining a satisfactory computational efficiency.

Interference cancellation analysis of output spectrum of virtual image phased array (VIPA) and application of VIPA in spontaneous Brillouin backscattering measurement

This paper mainly introduced a virtual image phased array (VIPA)-based Brillouin spectroscopy technology, analysed VIPA in principle, deduced the Brillouin shift calculation equations, analysed the output spectral characteristics of VIPA through simulation, and proposed the most effective way to avoid interference cancellation in the spectrum. We built a single-stage VIPA spontaneous Brillouin backscattering system, and made multiple measurements on water, ethanol and glycerol, and the measurement results are consistent with the theoretical values reported in other literature. Finally, it is compared with another method mentioned in the literature, and the results show that the method in this paper has higher accuracy.

Omni-Directional Pathloss Measurement Based on Virtual Antenna Array With Directional Antennas

Omni-directional pathloss, which refers to the pathloss when omni-directional antennas are used at the link ends, are essential for system design and evaluation. In the millimeter-wave (mm-Wave) and beyond bands, high gain directional antennas are widely used for channel measurements due to the significant signal attenuation. Conventional methods for omni-directional pathloss estimation are based on directional scanning sounding (DSS) system, i.e., a single directional antenna placed at the center of a rotator capturing signals from different rotation angles. The omni-directional pathloss is obtained by either summing up all the powers above the noise level or just summing up the powers of detected propagation paths. However, both methods are problematic with relatively wide main beams and high side-lobes provided by the directional antennas. In this correspondence, directional antenna based virtual antenna array (VAA) system is implemented for omni-directional pathloss estimation. The VAA scheme uses the same measurement system as the DSS, yet it offers high angular resolution (i.e. narrow main beam) and low side-lobes, which is essential for achieving accurate multipath detection in the power angle delay profiles (PADPs) and thereby obtaining accurate omni-directional pathloss. A measurement campaign was designed and conducted in an indoor corridor at 28-30 GHz to verify the effectiveness of the proposed method.

Auralisation of combined mitigation measures in railway pass-by noise

To reduce noise exposure along railway lines various combinations of noise mitigation measures can be considered. However, predicting and assessing their effects is non-trivial and the potential need for multiple measures is difficult to communicate to stakeholders. Auralisation is a promising tool that can help to support communication and decision-making, and enable psychoacoustic evaluations. This paper presents developments of a physics-based auralisation model for train pass-bys that allows various mitigation measures to be included. The work is conducted within the European research project SILVARSTAR. The proposed model includes contribution from rolling noise, impact noise, traction, auxiliary systems, and aerodynamic noise. It is physically based and allows a direct assessment of pass-by parameters such as speed, roughness, wheel flats and track design. Based on the TWINS model, five structural transfer paths for rolling noise are considered to integrate mitigation measures such as wheel and rail dampers. Shielding by noise barriers is simulated with analytical models. Reflection at different ground types is considered and can account for track embankments. The results can be coupled to an immersive Virtual Reality environment, by first panning the synthesised sounds to a small virtual speaker array and subsequently dynamic binaural rendering for headphones.

Curved Computer-Generated Integral Imaging Based on Backward Ray-Tracing Technique

In traditional computer-generated integral imaging (CGII) methods, the generated elemental image array (EIA) is flat, and it doesn't fit for curved integral imaging (II) systems. Here, a curved CGII method was proposed for curved II system. In the proposed method, multiple virtual camera arrays (VCAs) were built up to determine the origins and directions of the traced rays. Combined with the backward ray-tracing (BRT) technique, a curved EIA was generated, and the rendering time was the same as the BRT-CGII of flat II system. A curved II system consisting of a curved organic light emitting diode display screen, a curved lens array and a curved optical diffuser screen was built up in the experiment. The proposed curved CGII method generated correct curved EIA for the curved II system, and the system presented vivid 3D images with the viewing angle as wide as 80° × 50°.

Ternary redundant sparse linear array design with high robustness

Sparse linear array is prone to element failure affected by environmental and other factors in practical application, resulting in the decline of degrees of freedom and the attenuation or even failure of direction of arrival (DOA) estimation performance. To address this problem, a ternary redundant sparse array composed of three uniform linear arrays with different spacings at specific distances is designed, and the analytical expression of its degrees of freedom is derived. The configuration rules of the array are concise, and the difference coarrays of the array are hole-free. Mathematically proves that all virtual array elements can be covered with a weight of not less than 3 except the 4 farthest. The array has lower sensors importance and less generalized k-fragility. The array design takes into account the maximum degrees of freedom, redundancy and sparsity. In case of sensors failure, compared with the other sparse linear arrays, the array has more stable difference coarrays and higher uniform degrees of freedom. Compared with multiple-fold redundancy arrays, the array has lower mutual coupling. Simulation results show that the ternary redundant array has superior robustness and higher DOA estimation accuracy under sensors failure.

Beamforming of Rayleigh and Love Waves in the Course of Atlantic Cyclones

AbstractThe main sources of the ambient seismic wavefield in the microseismic frequency band (peaking in the ∼0.04–0.5 Hz range) are earth's oceans, namely the wind‐driven surface gravity waves (SGW) that couple oscillations into the seafloor and the upper crust underneath. Cyclones (e.g., hurricanes, typhoons) and other atmospheric storms are efficient generators of high ocean waves that in turn generate distinct microseismic signatures. In this study, we perform a polarization (i.e., three‐component) beamforming analysis of microseismic (0.05–0.16 Hz) retrograde Rayleigh and Love waves during major Atlantic hurricanes using a virtual array of seismometers in Eastern Canada. Oceanic hindcasts and meteorological data are used for comparison. No continuous generation of microseism along the hurricane track is observed but rather an intermittent signal generation. Both seismic surface wave types show clear cyclone‐related microseismic signatures that are consistent with a colocated generation at near‐coastal or shallow regions, however the Love wavefield is comparatively less coherent. We identify two different kinds of intermittent signals: (a) azimuthally progressive signals that originate with a nearly constant spatial lag pointing toward the trail of the hurricanes and (b) azimuthally steady signals remaining nearly constant in direction of arrival even days after the hurricane significantly changed its azimuth. This high complexity highlights the need for further studies to unravel the interplay between site‐dependent geophysical parameters, SGW forcing at depth and microseismic wavefield radiation and propagation, as well as the potential use of cyclone microseisms as passive natural sources.

Text classification in memristor-based spiking neural networks

Memristors, emerging non-volatile memory devices, have shown promising potential in neuromorphic hardware designs, especially in spiking neural network (SNN) hardware implementation. Memristor-based SNNs have been successfully applied in a wide range of applications, including image classification and pattern recognition. However, implementing memristor-based SNNs in text classification is still under exploration. One of the main reasons is that training memristor-based SNNs for text classification is costly due to the lack of efficient learning rules and memristor non-idealities. To address these issues and accelerate the research of exploring memristor-based SNNs in text classification applications, we develop a simulation framework with a virtual memristor array using an empirical memristor model. We use this framework to demonstrate a sentiment analysis task in the IMDB movie reviews dataset. We take two approaches to obtain trained SNNs with memristor models: (1) by converting a pre-trained artificial neural network (ANN) to a memristor-based SNN, or (2) by training a memristor-based SNN directly. These two approaches can be applied in two scenarios: offline classification and online training. We achieve the classification accuracy of 85.88% by converting a pre-trained ANN to a memristor-based SNN and 84.86% by training the memristor-based SNN directly, given that the baseline training accuracy of the equivalent ANN is 86.02%. We conclude that it is possible to achieve similar classification accuracy in simulation from ANNs to SNNs and from non-memristive synapses to data-driven memristive synapses. We also investigate how global parameters such as spike train length, the read noise, and the weight updating stop conditions affect the neural networks in both approaches. This investigation further indicates that the simulation using statistic memristor models in the two approaches presented by this paper can assist the exploration of memristor-based SNNs in natural language processing tasks.

An axial length measurement system based on the VIPA spectrometer

In the ophthalmology field, the length of the eye axis is an effective way to determine whether the eye is healthy or not. Thus, the accurate measurement of the axial length becomes very important. In this paper, a measurement system for axial length based on a virtual image phase array spectrometer is planned. This system has many advantages, such as short acquisition time, wide spectrum measurement variability, high spectral resolution, etc. With the advantages of it being non-invasive and the fact that it can be used in real time, the optical coherence tomography system can be used to enhance the speed of the interference image spectrum of the cornea and retina. By verifying the effectiveness of the system, eye samples with an axis length of 18–32 mm are measured accurately with a measurement error of ±0.07 mm and a minimum measurement length of around 0.55 mm. The optical power of the incident light entering the sample at a wavelength of 810 nm is measured by an optical power meter to be less than 710 μm, and the power of the reflected light from the sample is 95nW. Based on the data above, the measurement system in this paper is identified as a biometric instrument that complies with internationally accepted safety standards.

A new array extension configuration method based on nesting and minimum redundancy

AbstractWhile the uniform linear array (ULA) is a well‐known array configuration being widely used in various practical application scenarios, it also encounters numerous challenges in the field of direction‐of‐arrival (DOA) estimation. Specifically, it is difficult for the ULA to achieve a satisfactory DOA estimation accuracy, especially in the case of closely spaced sources. That is because that the resolvability of ULA is severely restricted by its limited DOA. To circumvent this issue and further improve the DOA estimation performance, a new array geometry is designed. Inspired by the fact that some linear sparse co‐arrays can yield higher DOFs and larger array apertures, the proposed array configuration is developed by nesting two or more minimum‐redundant arrays in a dedicated way. The simulation results indicate that the proposed array configuration can significantly increase the DOFs and the length of virtual array apertures, and an improved estimation accuracy can be accepted.

Direction of Arrival Estimation of Generalized Nested Array via Difference–Sum Co-Array

To address the weakness that the difference co-array (DCA) only enhances the degrees of freedom (DOFs) to a limited extent, a new configuration called the generalized nested array via difference-sum co-array (GNA-DSCA) is proposed for direction of arrival (DOA) estimation. We consider both the temporal and spatial information of the array output to construct the DSCA model, based on which the DCA and sum co-array (SCA) of the GNA are systematically analyzed. The closed-form expression of the DOFs for the GNA-DSCA is derived under the determined dilation factors. The optimal results show that the GNA-DSCA has a more flexible configuration and more DOFs than the GNA-DCA. Moreover, the larger dilation factors yield significantly wider virtual aperture, which indicates that it is more attractive than the reported DSCA-based sparse arrays. Finally, a hole-filling strategy based on atomic norm minimization (ANM) is utilized to overcome the degradation of the estimation performance due to the non-uniform virtual array, thus achieving accurate DOA estimation. The simulation results verify the superiority of the proposed configuration in terms of virtual array properties and estimation performance.

Application of a Virtual Magnetic Dipoles in Antenna Array to Increase the Direction Finding Accuracy

The article discusses the method of forming a virtual antenna array based on magnetic dipoles. To test the effectiveness of the formation of a virtual antenna array, a simulation of an unmanned aerial vehicle with a directionfinding complex of four vector antenna elements was carried out. To perform direction finding, two methods are considered ‒ based on the electric field and magnetic. On the basis of the study, it was found that the use of direction finding based on magnetic dipoles can significantly improve the stability and accuracy of the bearing for both linear and elliptical electromagnetic waves. The article presents the main mathematical expressions that are used to determine the characteristics of the direction finding, as well as the dependence of the bearings in the studied frequency range.

Broadband DOA Estimation by Exploiting DFT Extrapolation

This study proposes broadband direction (DOA) estimation through discrete Fourier transform (DFT) extrapolation. We used DFT extrapolation in the lower band and extended the sampled data to reduce the beam width in the spectral domain and improved the accuracy of the estimated DOA. The sampled data with a length of 12 were extrapolated to 36 by the addition of 12-element virtual arrays to 12 real arrays on both sides. The average RMSEs of the estimated DOAs were measured throughout the wide frequency band. To verify the validity of the proposed algorithm, we demonstrated that the RMSE obtained from the broadband DOA estimation for multiple signals of interest (SOIs) was reduced in the extrapolated array. It was demonstrated that the proposed algorithm can broaden the frequency band at which a fixed number of array can estimate the DOA accurately.

Structured Nyquist Correlation Reconstruction for DOA Estimation With Sparse Arrays

Sparse arrays are known to achieve an increased number of degrees-of-freedom (DOFs) for direction-of-arrival (DOA) estimation, where an augmented virtual uniform array calculated from the correlations of sub-Nyquist spatial samples is processed to retrieve the angles unambiguously. Nevertheless, the geometry of the derived virtual array is dominated by the specific physical array configurations, as well as the deviation caused by the practical unforeseen circumstances such as detection malfunction and missing data, resulting in a quite sensitive model for virtual array signal processing. In this paper, we propose a novel sparse array DOA estimation algorithm via structured correlation reconstruction, where the Nyquist spatial filling is implemented on the physical array with a compressed transformation related to its equivalent filled array to guarantee the general applicability. While the unknown correlations located in the whole rows and columns of the augmented covariance matrix lead to the fact that strong incoherence property is no longer satisfied for matrix completion, the structural information is introduced as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a prior</i> to formulate the structured correlation reconstruction problem for matrix reconstruction. As such, the reconstructed covariance matrix can be effectively processed with full utilization of the achievable DOFs from the virtual array, but with a more flexible constraint on the array configuration. The described estimation problem is theoretically analyzed by deriving the corresponding Cram´er-Rao bound (CRB). Moreover, we compare the derived CRB with the performance of the virtual array interpolation-based algorithm. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DOA estimation algorithm in terms of achievable DOFs, resolution, and estimation accuracy.

Coarray Tensor Completion for DOA Estimation

Sparse array direction-of-arrival (DOA) estimation using tensor model has been developed to handle multi-dimensional sub-Nyquist sampled signals. Furthermore, augmented virtual arrays can be derived for Nyquist-matched coarray tensor processing. However, the partially augmentable sparse array corresponds to a discontinuous virtual array, whereas the existing methods can only utilize its continuous part. Conventional virtual linear array interpolation techniques complete coarray covariance matrices with dispersed missing elements, but fail to complete the coarray tensor with whole missing slices. In this paper, we propose a coarray tensor completion algorithm for two-dimensional DOA estimation, where the coarray tensor statistics can be entirely exploited. In particular, in order to impose an effective low-rank regularization on the slice-missing coarray tensor, we propose shift dimensional augmenting and coarray tensor reshaping approaches to reformulate a structured coarray tensor with sufficiently dispersed missing elements. Furthermore, the shape of the reformulated coarray tensor is optimized by maximizing the dispersion-to-percentage ratio of missing elements. As such, a coarray tensor nuclear norm minimization problem can be designed to optimize the completed coarray tensor corresponding to a filled virtual array, based on which the closed-form DOA estimation is achieved. Meanwhile, the global convergence of the coarray tensor completion is theoretically proved. Simulation results demonstrate the effectiveness of the proposed algorithm compared to other matrix-based and tensor-based methods.

A computational modeling framework for pre-clinical evaluation of cardiac mapping systems.

There are a variety of difficulties in evaluating clinical cardiac mapping systems, most notably the inability to record the transmembrane potential throughout the entire heart during patient procedures which prevents the comparison to a relevant "gold standard". Cardiac mapping systems are comprised of hardware and software elements including sophisticated mathematical algorithms, both of which continue to undergo rapid innovation. The purpose of this study is to develop a computational modeling framework to evaluate the performance of cardiac mapping systems. The framework enables rigorous evaluation of a mapping system's ability to localize and characterize (i.e., focal or reentrant) arrhythmogenic sources in the heart. The main component of our tool is a library of computer simulations of various dynamic patterns throughout the entire heart in which the type and location of the arrhythmogenic sources are known. Our framework allows for performance evaluation for various electrode configurations, heart geometries, arrhythmias, and electrogram noise levels and involves blind comparison of mapping systems against a "silver standard" comprised of computer simulations in which the precise transmembrane potential patterns throughout the heart are known. A feasibility study was performed using simulations of patterns in the human left atria and three hypothetical virtual catheter electrode arrays. Activation times (AcT) and patterns (AcP) were computed for three virtual electrode arrays: two basket arrays with good and poor contact and one high-resolution grid with uniform spacing. The average root mean squared difference of AcTs of electrograms and those of the nearest endocardial action potential was less than 1ms and therefore appears to be a poor performance metric. In an effort to standardize performance evaluation of mapping systems a novel performance metric is introduced based on the number of AcPs identified correctly and those considered spurious as well as misclassifications of arrhythmia type; spatial and temporal localization accuracy of correctly identified patterns was also quantified. This approach provides a rigorous quantitative analysis of cardiac mapping system performance. Proof of concept of this computational evaluation framework suggests that it could help safeguard that mapping systems perform as expected as well as provide estimates of system accuracy.

Разработка программного обеспечения радара с виртуальной антенной решеткой на платформе Digilent Zedboard

MIMO technology allows you to create virtual antenna arrays, significantly reducing the number of receiving and transmitting channels compared to classical phased antenna arrays (PAA). At the same time, the characteristics of the antenna system (width of the radiation pattern, gain factor) and, as a result, the characteristics of the radar (angular resolution, detection range) are preserved. Reducing the number of receiving and transmitting channels leads to a significant reduction in the cost of the radar as a whole. The article describes the process of developing a mathematical model and signal processing software based on the Digilent Zedboard platform. The results of modeling and testing of the hardware and software implementation of the processing algorithm are presented. The degree of loading of the Xilinx Zynq XC7Z020 crystal standing on the Digilent Zedboard platform is estimated.