Robust Microphone Placement for Source Localization from Noisy Distance Measurements (original) (raw)
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Sound positioning using a small-scale linear microphone array
International Conference on Indoor Positioning and Indoor Navigation, 2013
Microphone arrays, also known as acoustic antennas, have been extensively used for sound localization. Small-scale microphone arrays have especially been used in teleconferences and game consoles due to their small dimension and easy deployment. In this article, we present an approach to locating a sound source using a small linear microphone array. We describe the fundamentals of linear microphone arrays and analyze the impact of geometry in terms of positioning accuracy using the dilution of precision (DOP) concept. The generalized cross-correlation (GCC) based on the phase transform (PHAT) weighting function is used to estimate the time difference of arrivals in a microphone array. Given the time differences, we use both closed-form and iterative optimization solutions to calculate the coordinates of the sound source. In order to evaluate the performances of the solutions applied in this paper, simulations and field tests were conducted. Simulation results show that the closed-form algorithm gives a positioning error of less than 5 cm in a 10by-10 meter room when the geometry of a microphone array is good and the signal to noise ratio (SNR) is high. Linear small microphone arrays have lower performances compared to a non-linear distributed array. When the scale of a linear array is reduced, the positioning accuracy decreases dramatically. With a small linear array, the iterative optimization algorithm gives much better performance compared to the closed-form algorithm. Field tests were conducted in an 11-by-5.6 meter room using a linear array with a length of 0.23 meters. Positioning results show an average error of 0.25 meters along the axis parallel to the linear array and 0.53 meters error along the axis which is perpendicular to the linear array.
Discriminability Measure for Microphone Array Source Localization
2012
The performance of sound source localization systems based on microphone arrays is dictated by a combination of factors that range from array, source, and environmental characteristics to the nature of the localization algorithm itself. Array geometry is an example of critical feature for source localizability. This paper proposes a numerical measure of the capability of a microphone array with a specific geometry to distinguish a given point in space from its neighbors. Such numerical measure, herein called discriminability index (D), has the interesting feature of taking into account only the effects of array geometry on spatial resolution, thus providing a way of connecting a microphone array geometry to the region of interest. The proposed measure can be particularly useful to help choose an appropriate array geometry when a sound source is confined to a predefined region. Simulation results using the classic SRP-PHAT method are presented for highlighting the correlation between D and the accuracy of the source location estimates.
Robotics and Autonomous Systems, 2019
Human-robot interaction in natural settings requires filtering out the different sources of sounds from the environment. Such ability usually involves the use of microphone arrays to localize, track and separate sound sources online. Multimicrophone signal processing techniques can improve robustness to noise but the processing cost increases with the number of microphones used, limiting response time and widespread use on different types of mobile robots. Since sound source localization methods are the most expensive in terms of computing resources as they involve scanning a large 3D space, minimizing the amount of computations required would facilitate their implementation and use on robots. The robot's shape also brings constraints on the microphone array geometry and configurations. In addition, sound source localization methods usually return noisy features that need to be smoothed and filtered by tracking the sound sources. This paper presents a novel sound source localization method, called SRP-PHAT-HSDA, that scans space with coarse and fine resolution grids to reduce the number of memory lookups. A microphone directivity model is used to reduce the number of directions to scan and ignore non significant pairs of microphones. A configuration method is also introduced to automatically set parameters that are normally empirically tuned according to the shape of the microphone array. For sound source tracking, this paper presents a modified 3D Kalman (M3K) method capable of simultaneously tracking in 3D the directions of sound sources. Using a 16-microphone array and low cost hardware, results show that SRP-PHAT-HSDA and M3K perform at least as well as other sound source localization and tracking methods while using up to 4 and 30 times less computing resources respectively.
Microphone arrays application in three-dimensional sound source localisation
International Journal of Intelligent Information and Database Systems, 2012
This article describes the problems of use of spatial microphone arrays in sound source location. Questions concerning modelling of planar (2-D) and spatial (3-D) directional characteristics of microphone arrays are discussed. Typical algorithms used in SSL system are also described. The paper describes options to use a single point surround microphone to determine a direction of the sound source localisation. A 'soundfield' microphone with four transducers (capsules) characterised by cardioid directivity pattern. A unique mechanical design of the transducer results in its omnidirectional directivity pattern. The microphone enables 3-D sound acquisition in so called A-format. Upon further processing of signal it is possible to determine, e.g., a direction of a sound source within space. The conducted experiments prove that a simple calculation algorithm is in particular feasible for a real time operation, and application of the soundfield microphone significantly simplifies mechanical design of the SSL system.
The Effect of Calibration Errors on Source Localization with Microphone Arrays
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007
Source localization employing time-differences-of-arrival has been employed for many applications. The accuracy of source localization is limited by the errors in the time differences of arrival estimation as well as microphone position calibration errors. Because a microphone position error will affect multiple time differences of arrival, correlation between these quantities will be introduced. This work presents a new mathematical framework
Microphone array positioning technique with Euclidean distance geometry
Applied Acoustics, 2020
Source localization and quantification by an acoustic array of microphones depend to a great extent on an accurate knowledge of the antenna position towards the radiating device. The present work details a methodology to determine the location of the microphones in relation to an object of study, starting from its geometric shape and that of the array, in order to reproduce an experimental configuration in any retro-propagating method. A set of reference sources are placed on several prominent locations of the device to estimate the times of flight (ToF) (and distances) between them and the microphones, connecting the array and the object together. The overall geometric configuration is thus defined by an Euclidean Distance Matrix (EDM), which is basically the matrix of squared distances between points. First, MultiDimensional Unfolding (MDU) technique is used to reconstruct the point set from distances. Second, this point set is then aligned with the device, using reference sources as anchor nodes. This orthogonal Procustes problem is solved by the Kabsch algorithm to obtain the optimal rotation and translation matrices between the coordinate system of the array and that of the object of study. The methodology is detailed, validated first by a numerical simulation of a typical experimental setup. An experimental campaign is finally carried out to assess the robustness of the method in a typical test case.
Sound Localization for Ad-Hoc Microphone Arrays
Energies, 2021
Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Prev...
Diffusion-Based Sound Source Localization Using Networks of Planar Microphone Arrays
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In this work, we propose a novel approach for distributed 3D sound source localization and tracking based on networks of planar microphone arrays, each of which estimates a 2D Direction Of Arrival (DOA). The proposed method is computationally distributed and eliminates the need for a specialized node to collect and process all information. Sound source localization is achieved by considering the task as a distributed optimization problem approached using the Adapt Then Combine (ATC) diffusion technique. This approach also allows the development of cooperation strategies between sensor nodes (i.e., microphone arrays). We propose the use of a cooperation strategy that improves the localization accuracy by exploiting the estimated error statistics of each sensor node and penalizing the noisy arrays. We then evaluate the proposed approach in terms of localization accuracy and robustness to noisy sensor measurements.
Sound Source Localization with Non-calibrated Microphones
Lecture Notes in Computer Science, 2008
We propose a new method for localizing a sound source in a known space with non-calibrated microphones. Our method does not need the accurate positions of the microphones that are required by traditional sound source localization. Our method can make use of wide variety of microphone layout in a large space because it does not need calibration step on installing microphones. After a number of sampling points have been stored in a database, our system can estimate the nearest sampling point of a sound by utilizing the set of time delays of microphone pairs. We conducted a simulation experiment to determine the best microphone layout in order to maximize the accuracy of the localization. We also conducted a preliminary experiment in real environment and obtained promising results.