DOA estimation method for an arbitrary triangular microphone arrangement

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 200

A DOA Estimation Method For an Arbitrary Triangular Microphone Arrangement

This paper proposes a new DOA (direction of arrival) estimation method for an arbitrary triangular microphone arrangement. Using the phase rotation factors for the crosscorrelations between the adjacent-microphone signals, a general form of the integrated cross spectrum is derived. DOA estimation is reduced to a non-linear optimization problem of the general integrated cross spectrum. It is shown that a conventional DOA estimation for the equilateral triangular microphone arrangement is a special case of the proposed method. Sensitivity to the relative time-delay is derived in a closed form and demonstrated for different microphone arrangements. Simulation results demonstrate that the deviation of estimation error in the case of 20 dB SNR is less than 1 degree which is comparable to high resolution DOA estimation methods

Bimodal sound source tracking applied to road traffic monitoring

The constant increase of road traffic requires closer and closer road network monitoring. The awareness of traffic characteristics in real time as well as its historical trends, facilitates decision-making for flow regulation, triggering relief operations, ensuring the motorists’ safety and contribute to optimize transport infrastructures. Today, the heterogeneity of the available data makes their processing complex and expensive (multiple sensors with different technologies, placed in different locations, with their own data format, unsynchronized, etc.). This leads metrologists to develop “smarter” monitoring devices, i.e. capable of providing all the necessary data synchronized from a single measurement point, with no impact on the flow road itself and ideally without complex installation. This work contributes to achieve such an objective through the development of a passive, compact, non-intrusive, acoustic-based system composed of a microphone array with a few number of elements placed on the roadside. The proposed signal processing techniques enable vehicle detection, the estimation of their speed as well as the estimation of their wheelbase length as they pass by. Sound sources emitted by tyre/road interactions are localized using generalized cross-correlation functions between sensor pairs. These successive correlation measurements are filtered using a sequential Monte Carlo method (particle filter) enabling, on one hand, the simultaneous tracking of multiple vehicles (that follow or pass each other) and on the other hand, a discrimination between useful sound sources and interfering noises. This document focuses on two-axle road vehicles only. The two tyre/road interactions (front and rear) observed by a microphone array on the roadside are modeled as two stochastic, zero-mean and uncorrelated processes, spatially disjoint by the wheelbase length. This bimodal sound source model defines a specific particle filter, called bimodal particle filter, which is presented here. Compared to the classical (unimodal) particle filter, a better robustness for speed estimation is achieved especially in cases of harsh observation. Moreover the proposed algorithm enables the wheelbase length estimation through purely passive acoustic measurement. An innovative microphone array design methodology, based on a mathematical expression of the observation and the tracking methodology itself is also presented. The developed algorithms are validated and assessed through in-situ measurements. Estimates provided by the acoustical signal processing are compared with standard radar measurements and confronted to video monitoring images. Although presented in a purely road-related applied context, we feel that the developed methodologies can be, at least partly, applied to rail, aerial, underwater or industrial metrology

Application of sound source separation methods to advanced spatial audio systems

This thesis is related to the field of Sound Source Separation (SSS). It addresses the development and evaluation of these techniques for their application in the resynthesis of high-realism sound scenes by means of Wave Field Synthesis (WFS). Because the vast majority of audio recordings are preserved in twochannel stereo format, special up-converters are required to use advanced spatial audio reproduction formats, such as WFS. This is due to the fact that WFS needs the original source signals to be available, in order to accurately synthesize the acoustic field inside an extended listening area. Thus, an object-based mixing is required. Source separation problems in digital signal processing are those in which several signals have been mixed together and the objective is to find out what the original signals were. Therefore, SSS algorithms can be applied to existing two-channel mixtures to extract the different objects that compose the stereo scene. Unfortunately, most stereo mixtures are underdetermined, i.e., there are more sound sources than audio channels. This condition makes the SSS problem especially difficult and stronger assumptions have to be taken, often related to the sparsity of the sources under some signal transformation. This thesis is focused on the application of SSS techniques to the spatial sound reproduction field. As a result, its contributions can be categorized within these two areas. First, two underdetermined SSS methods are proposed to deal efficiently with the separation of stereo sound mixtures. These techniques are based on a multi-level thresholding segmentation approach, which enables to perform a fast and unsupervised separation of sound sources in the time-frequency domain. Although both techniques rely on the same clustering type, the features considered by each of them are related to different localization cues that enable to perform separation of either instantaneous or real mixtures.Additionally, two post-processing techniques aimed at improving the isolation of the separated sources are proposed. The performance achieved by several SSS methods in the resynthesis of WFS sound scenes is afterwards evaluated by means of listening tests, paying special attention to the change observed in the perceived spatial attributes. Although the estimated sources are distorted versions of the original ones, the masking effects involved in their spatial remixing make artifacts less perceptible, which improves the overall assessed quality. Finally, some novel developments related to the application of time-frequency processing to source localization and enhanced sound reproduction are presented.Cobos Serrano, M. (2009). Application of sound source separation methods to advanced spatial audio systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8969Palanci

Modelling, Simulation and Data Analysis in Acoustical Problems

Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years