Auralization of Musical Instruments in Virtual Halls Considering Source Directivity

Most methods of radio emission source localization are based on an estimation of received signal parameters. Evaluation of signal reception direction is used in a method called a direction of arrival (DOA). The DOA is one of the most commonly used location methods in wireless systems. Its important advantage is independence from knowledge of a time-frequency structure of the received signal. Therefore, this method is used primarily in military radio reconnaissance systems and electronic warfare. In this paper, we evaluate errors in determining the DOA resulting from propagation phenomena occurring in an urbanized environment. A maximum power received from a given direction is the basis for the estimation of the DOA in most radio direction-finders. Thus, the direction of maximum radiation of the localized object is important because it causes a change of the extremum in a power azimuth spectrum (PAS). Simulation studies are the basis for assessing the DOA error for the transmitters with the directional antennas. To model the impact of propagation phenomena, a multi-elliptical model is used. This model considers the majority of propagation phenomena occurring in the urbanized environment. The possibility of considering patterns of the transmitting and receiving antenna is its important advantage. In this case, the Gaussian is used to model the pattern of the directional antennas. The assessment of the DOA error is carried out for non-line-of-sight conditions between the receiver and transmitter, i.e., the radio direction-finder and localized object, respectively. In simulation studies, the influence of the transmitting antenna parameters, i.e., its beamwidth and direction of maximum radiation, on a shape of the received PASs and their extremums is considered.

In order to solve the problem that the channel gain-phase mismatch would deteriorate the performance of direction of arrival (DOA) estimation in actual direction finding (DF) system, a novel efficient gain-phase calibration algorithm based on the self-checking signal is proposed in this paper. By injecting a self-checking signal into the actual DF system, the whole calibration process could divide into the off-line pre-calibration and the auto-calibration part. Thus, it could realize the real-time auto-calibration efficiently during the DOA estimation process. Moreover, in order to verify the effectiveness of the proposed method, a practical DF signal processor based on the FPGA and DSP is implemented in this paper, and the experiments are carried out in the anechoic chamber. The experiment result shows that the proposed method could calibrate the gain-phase mismatch in real-time and have higher DOA estimation accuracy.

A class of methods is presented for wholly estimating direction of arrival (DOA) of convolutively mixed sources in the frequency domain, which is based on independent component analysis (ICA). Convolutive mixtures of multiple sources in the spatio-temporal domain are firstly reduced to instantaneous mixtures by using the well-known short-time Fourier transformation (STFT) technique. From the time-frequency mixture in each frequency bin, one frequency respond matrix of the mixing system from sources to sensors is identified by some instantaneous ICA algorithms. Furthermore, DOAs of the multiple sources is estimated by using a whole estimating strategy. Consequently, all mixtures in total frequency bins contribute to a final estimation set, in which the source directions are shown as several direction clusters and/or local maxima. Experimental results indicate that the ICA based methods have some advantages over the well-known MUSIC (MUltiple SIgnal Classification) method not only on estimation precision of multiple source directions, but also on potential applicability under some especial conditions.

In this paper, we propose a composite right/left handed two port leaky-wave antenna (CRLH-LWA) having reduced size and enhanced beam steering capabilities. The antenna is made of a cascade of metamaterial CRLH unit cells, populated with varactor diodes. By properly designing the CRLH unit cell, the propagation constant has been optimized within the radiated zone achieving maximum beam steering and keeping a nearly constant gain for all of the beam configurations. Through a modified multiple signal classification (MUSIC) algorithm, we employed the antenna for direction of arrival (DoA) estimation. Validation of the algorithm along with the proposed CRLH-LWA has been conducted in an anechoic chamber and the estimated DoA results are in good agreement with the predicted angles.

In this paper, we have proposed a low-cost self-localization method which uses 4 elements of microphones, wheel rotation and sound sources as beacons, whose absolute location and frequency bands are known. The proposed method consists of following 4 steps. The proposed method (i) execute self-localization using wheel-based odometry, (ii) estimate direction-of-arrival (DOA) of the sound sources using sounds recorded by the elements of the microphone array, (iii) predict the DOA of the sound sources from estimated location and pose, and (iv) conduct self-localization by integrating all of the information. To evaluate the proposed method, experiments were conducted. The proposed method was compared to the conventional methods, which were wheel-based odometry and self-localization using only DOA. In the experiments, we have supposed the house-cleaning robot and its trajectory. As results, without any obstacles or walls, the mean of the estimation errors by wheel-based odometry were 670 mm and 0.08 rad, and those of self-localization using only DOA were 2870 m and 0.07 rad in the worst case. In contrast with these methods, proposed method results in 69 mm, 0.02 rad as the worst estimation error of self location and pose. From the result with occlusion of a sound source, the mean of the localization error increased 60 mm, as the proposed method detects the incorrect DOA and prevents it from estimation. From the result with reflective wave from wall, there was a place where the localization error was large. The cause of this error was considered as directivity of sound source. These results indicate that the proposed method is feasible under indoor environment.

Beamspace MUSIC (multiple signal classification) of forward-backward spatial smoothing are used to estimate the directions of coherent arrivals. Coherence are often encountered in sonar, radar, or mobile communications. Such combination can be degraded when the source signals become coherent or strongly correlated. In this paper, we improve angular resolution of beamspace MUSIC by using the forward-backward averaging of a combined signal eigenvectors. The sample covariance matrix computed from the forward-backward spatial smoothing is exploited for an eigen-decomposition. The decorrelation performance of the proposed method is compared to the several methods based on MUSIC and on beamspace MUSIC, in terms of directions of arrival (DOA) estimations, MSEs versus (1) correlation, (2) noise variance and (3) SNRs, probability of resolution to separate closely spaced DOAs.

Acoustic emissions from underwater sources are used to detect, locate, and track targets by passive surveillance sensors. The “vector” sensors measure the scalar pressure as well as the orthogonal components of particle velocity and offer distinct advantages over the traditional solution of array of hydrophones due to their smaller size and frequency independent performance over the frequency range specified for constituent elements. This paper presents studies on an in-house implemented prototype vector sensor employing tri-axial accelerometer as constituent element. The tests undertaken include Direction of Arrival (DoA) estimation and application of modified Fast Orthogonal Search technique on a single Vector Sensor for improvement in spectral resolution. We also propose a configuration involving just two Vector Sensors (composed solely of accelerometers) that offers ease of design and obviates the requirement of a pressure sensor in setup for obtaining DoA estimate while also providing range to the source.

In this paper, localization and separation of acoustic sources are examined. Depending on the number of sources in relation to the array channels, the problem is investigated in terms of underdetermined and overdetermined configurations. In the underdetermined configuration, virtual monopole sources are assumed in uniformly spaced angles. The problem is then formulated into compressive sampling (CS) problem which can be solved by using the linearly constrained -norm convex (CVX) optimization. The solution yields the directions of real sources and the source signal spectrum, which enables localization and reconstruction of sources at one shot. In the underdetermined configuration, source localization and signal separation is carried out in two steps. First, the directions of arrival (DOA) are estimated with Minimum Variance Distortionless Response (MVDR) or Multiple Signal Classification (MUSIC). Next, Tikhonov regularization (TIKR) is utilized to recover the source spectrum. In the localization problem for both configurations, Neyman-Pearson detector is employed to determine thresholds for source detection. Numerical and experimental results show that the proposed methods produce improved speech quality in terms of mean opinion score (MOS) in perceptual evaluation of speech quality (PESQ) test.

In this paper, we present an experimental study evaluating the performance of a reconfigurable antenna element for direction-of-arrival (DOA) estimation in wireless systems. We consider a reconfigurable antenna with directive radiation pattern and an electronic control mechanism to continuously scan its beam over the space. We implement a MUSIC-type algorithm which estimates the DOA using samples collected from different configurations (scanning steps) of the antenna radiation pattern. All experiments were carried out in an anechoic chamber using an actual reconfigurable antenna for different number of scanning steps. The results confirm the successful estimation of the DOA even with two scanning steps.

At the Defence Research Establishment of Sweden (FOA) an experimental S-band receiving digital array antenna for radar applications has been designed and built. It consists of a horizontal uniform linear array (ULA) of 12 antenna elements, whose digitized signals are processed in non-real time in a computer. Accurate calibration is utilized. We have compared several spectral and parametric direction-of-arrival (DOA) estimation methods for varying DOA separations, number of samples and signal-to-noise ratios (SNR) on measured data from an anechoic chamber. At ideal conditions the resolution can be improved considerably with model based DOA methods compared to conventional beamforming. We achieved a resolution below 1/10 of the resolution of conventional beamforming.

In this paper, we have introduced a new method to improve overall efficiency of direction-of-arrival (DoA) estimation scheme relying on received signal strength (RSS) values measured at the output port of electronically steerable parasitic array radiator (ESPAR) antenna. The proposed approach uses software-defined radio (SDR) setup and power pattern cross-correlation (PPCC) estimator involving multiple calibration planes. By placing the calibration planes using the proposed SDR-based iterative method, it has been possible to obtain more optimal form of the PPCC estimator, than originally proposed in the literature. Anechoic chamber measurements of our ESPAR antenna prototype indicate that one can keep the expected overall accuracy of DoA estimation results in a wide span of incoming signal elevation angles and, simultaneously, decrease the number of required calibration planes by more than half, which will shorten the time required for RSS-based DoA estimation process and also for the initial calibration procedure within an anechoic chamber.

In this paper, we report the evaluation of the performance of the methods for estimating the direction of arrival (DoA) with a virtual planar array antenna by conducting simulations and experiments in an anechoic chamber. These methods estimate the DOA of the arrival waves by synthesizing data received by a virtual planar array. First, we describe methods for synthesizing the data received by the virtual planar array using a T-shaped array antenna. Next, we present the simulation results that confirmed that the accuracy of these methods based on the virtual planar array. Finally, we demonstrate the effectiveness of the proposed systems through experiments in the anechoic chamber

In the field of array signal processing, direction of arrival (DOA) estimation is a prime area of research. DOA estimation and adaptive beamforming (ABF) are the main issues in smart antennas, which dynamically find the direction of desired and interfering users and finds the optimum weights for beamforming. There are numerous spectral and eigen structure algorithms for estimating the direction of narrow band sources. However, in a complex multipath channel environment, received signals from different directions are fully or partially correlated, which prevents the applications of high resolution techniques to estimate the direction of incoming signals. Maximum likelihood (ML) is an efficient technique for DOA estimation in a low signal to noise ratio (SNR) and coherent channel environment. In this paper, we use particle swarm optimization (PSO) for estimating ML solution by optimizing complex non linear multimodal function over a high dimensional space in linear arrays. PSO-ML estimator has been compared with conventional DOA estimation techniques in uncorrelated, partially correlated and coherent channel environment. The performance of PSO-ML estimator and conventional algorithms are analyzed in varying partially correlated channel environment. The simulation results demonstrate that PSO based estimator gives superior statistical performance.

We propose a new methodology of DOA (direction of arrival) estimation named SPIRE (Stepwise Phase dIfference REstoration) that is able to estimate sound source directions even if there is more than one source in a reverberant environment. DOA estimation in reverberant environments is difficult because the variance of the direction of an estimated sound source increases in reverberant environments. Therefore, we want the distance between microphones to be long. However, because of the spatial aliasing problem, the distance cannot be longer than half the wavelength of the maximum frequency of a source. DOA estimation performance of SPIRE is not limited by the spatial aliasing problem. The major feature of SPIRE is restoration of the phase difference of a microphone pair (M1) by using the phase difference of another microphone pair (M2) under the condition that the distance between the M1 microphones is longer than the distance between the M2 microphones. This restoration process enables the reduction of the variance of an estimated sound source direction and can alleviates the spatial aliasing problem that occurs with the M1 phase difference using direction estimation of the M2 microphones. The experimental results in a reverberant environment (reverberation time =about 300ms) indicate that even when there are multiple sources, the proposed method can estimate the source direction more accurately than conventional methods. In addition, DOA estimation performance of SPIRE with the array length 0.2m is shown to be almost equivalent to that of GCC-PHAT with the array length 0.5m. SPIRE can executes DOA estimation with a smaller microphone array than GCC-PHAT. From the viewpoint of the hardware size and coherence problem, the array length is required to be as small as possible. This feature of SPIRE is preferable.

Humans rely on detecting and recognizing surrounding sounds, a complex task due to the variability, mobility, and contextual diversity of auditory stimuli.This study investigates human perception of speech source positionencompassing both direction of arrival (DOA) and distance-by addressing the question: "Does the directivity of a speech source influence human spatial perception?"A listening test was conducted comparing omnidirectional and directional speech sources.Stimuli were generated using an acoustic virtual reality framework (RAVEN) under various conditions: two reverberation times (0.1 and 0.6 seconds), 8 DOA angles (0, 30, 90, 150, 180, 210, 270, 330), and two source types (omnidirectional and directional).Participants estimated the perceived direction and distance of the stimuli in a controlled environment.Findings from this study enhance the understanding of how source directivity impacts spatial perception in humans, providing a benchmark for the performance of artificial neural networks in similar tasks.These insights have potential applications in the design of immersive auditory experiences, hearing aids, and spatial audio systems that bridge human perception and machine learning models.It also contributes to the understanding of the mechanisms that central auditory processing exerts to manage sound localization, which could have future clinical applications.