Considerations on acoustic source localization (original) (raw)
Related papers
Real Time Acoustic Source localization of Emergency Signals
—In this paper, we have chronicled the development of sound localization system based on TDOA (Time Difference of Arrival). Acoustic Source Localization (ASL) is a technique used to track and locate the exact location of a sound source using an array of microphones. The concept of ASL uses sound signals captured from an array of microphones and they are processed using TDOA localization method to estimate the probable direction of sound source w.r.t to the microphone location. TDOA algorithm is a time delay estimation technique which estimates the time difference in the signal received at each microphone pair. These time delays obtained are then used in the Linear Least Squares (LSQR) Algorithm to estimate the source position w.r.t the microphone array. This system is implemented in real-time by using an on-board DSP processor TMS320C6748.
Precision and accuracy of acoustic gunshot location in an urban environment
ArXiv, 2021
The muzzle blast caused by the discharge of a firearm generates a loud, impulsive sound that propagates away from the shooter in all directions. The location of the source can be computed from time-of-arrival measurements of the muzzle blast on multiple acoustic sensors at known locations, a technique known as multilateration. The multilateration problem is considerably simplified by assuming straight-line propagation in a homogeneous medium, a model for which there are multiple published solutions. Live-fire tests of the ShotSpotter gunshot location system in Pittsburgh, PA were analyzed off-line under several algorithms and geometric constraints to evaluate the accuracy of acoustic multilateration in a forensic context. Best results were obtained using the algorithm due to Mathias, Leonari and Galati under a two-dimensional geometric constraint. Multilateration on random subsets of the participating sensor array show that 96% of shots can be located to an accuracy of 15 m or bette...
Acoustic source localization in sensor networks with low communication bandwidth
2006 International Workshop on Intelligent Solutions in Embedded Systems, 2006
A new acoustic localization scheme is proposed, which can be applied in sensor networks with low communication bandwidth. The first step of the two-stage algorithm is distributed and is evaluated at the sensors having possibly low communication capabilities. The sensors detect various events in the acoustic signal and transmit only the event descriptors to the base station where the sensor fusion is calculated in the second step using a novel generalized consistency function. Test results validate the performance of the proposed system in a noisy and reverberant environment. According to experiments, the proposed system decreases the necessary communication bandwidth with multiple orders of magnitude and still provides high accuracy comparable with that of the sophisticated beam-forming methods.
In recent years, there has been an increasing interest in the use of acoustic sensors for monitor-ing urban noise. The most common concerns are the exposure of civilians to high sound levels and the localization of the main noise sources. Pressure-based solutions have been proven useful for observing noise at specific locations, but they have limited capabilities addressing source localization in broad areas, especially transient noises. In contrast, the combination of pressure and particle velocity transducers, the use of vector sensor such as the Acoustic-Multi-Mission Sensor (AMMS), allows for the determination of the sound direction of arrival at one specific location. Consequently, a set of AMMS distributed across an area of interest enable the location of noise sources by using triangulation upon the acquired data. A monitoring system based on AMMS has been successfully tested for the detection of illegal fireworks in the city of Leiden (the Netherlands). Five sensors have bee...
Source localization with acoustic vector sensors
In this paper a localization method is analyzed, which uses Acoustic Vector Sensors (AVS). An AVS measures the directed velocity and the pressure in an area approaching a single point. In order to localize sound sources, the Multiple Signal Classification (MUSIC) was applied, which determines the signal and the noise components. MUSIC only uses the noise components (Noise Subspace) to estimate the direction of arrival. To estimate the quality of this method, the accuracy and the resolution of the localization were compared with an established pressure-based method. The accuracy and resolution of the AVS-based method are higher. MUSIC was more robust against calibration errors of phase and frequency. Our measurements showed that the combination of AVS, and MUSIC provides an efficient localization system.
Localization of Sound Sources: A Systematic Review
Energies
Sound localization is a vast field of research and advancement which is used in many useful applications to facilitate communication, radars, medical aid, and speech enhancement to but name a few. Many different methods are presented in recent times in this field to gain benefits. Various types of microphone arrays serve the purpose of sensing the incoming sound. This paper presents an overview of the importance of using sound localization in different applications along with the use and limitations of ad-hoc microphones over other microphones. In order to overcome these limitations certain approaches are also presented. Detailed explanation of some of the existing methods that are used for sound localization using microphone arrays in the recent literature is given. Existing methods are studied in a comparative fashion along with the factors that influence the choice of one method over the others. This review is done in order to form a basis for choosing the best fit method for our...
IJERT-Acoustic Localization Sensor for Embedded Surveillance Systems
International Journal of Engineering Research and Technology (IJERT), 2015
https://www.ijert.org/acoustic-localization-sensor-for-embedded-surveillance-systems https://www.ijert.org/research/acoustic-localization-sensor-for-embedded-surveillance-systems-IJERTV4IS100112.pdf Nowadays acoustic perception in intelligent home applications, surveillance systems and autonomous robots are gaining great popularity. Many robotic devices are currently equipped with embedded acoustic sensors. This sound based localization also find enormous application in military as well as security systems. In this paper sound source localization is implemented in analog circuit and also TOA (Time Of Arrival) estimation of sound is done in Matlab Simulink. TOA estimation is done based on GCC-PHAT algorithm.
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2013
Source Localization is a very well established technique that has a wide range of applications from remote sensing to the Global Positioning System. Sound source localization techniques are used in commercial applications like improving speech quality in hands free telephony, video conferencing to military applications like SONAR, surveillance systems and devices to locate the sources of artillery fire. A method is proposed to localize an acoustic source within a frequency band from 100Hz to 4 KHz in two dimensions using microphone array by calculating the direction of arrival (DOA) of the acoustic signals. Direction of arrival (DOA) estimation of acoustic signals using a set of spatially separated microphones uses the phase information present in signals. For this the time-delays are estimated for each pair of microphones in the array. From the known array geometry and the direction of arrival, the location of source can be obtained.
Direction of Arrival Estimation and Localization Using Acoustic Sensor Arrays
Journal of Sensor Technology, 2011
Sound source localization has numerous applications such as detection and localization of mechanical or structural failures in vehicles and buildings or bridges, security systems, collision avoidance, and robotic vision. The paper presents the design of an anechoic chamber, sensor arrays and an analysis of how the data acquired from the sensors could be used for sound source localization and object detection. An anechoic chamber is designed to create a clean environment which isolates the experiment from external noises and reverberation echoes. An FPGA based data acquisition system is developed for a flexible acoustic sensor array platform. Using this sensor platform, we investigate direction of arrival estimation and source localization experiments with different geometries and with different numbers of sensors. We further present a discussion of parameters that influence the sensitivity and accuracy of the results of these experiments.
Intelligent location of simultaneously active acoustic emission sources: Part I
Aircraft engineering, 2003
The intelligent acoustic emission locator is described in Part I, while Part II discusses blind source separation, time delay estimation and location of two simultaneously active continuous acoustic emission sources. The location of acoustic emission on complicated aircraft frame structures is a difficult problem of non-destructive testing. This article describes an intelligent acoustic emission source locator. The intelligent locator comprises a sensor antenna and a general regression neural network, which solves the location problem based on learning from examples. Locator performance was tested on different test specimens. Tests have shown that the accuracy of location depends on sound velocity and attenuation in the specimen, the dimensions of the tested area, and the properties of stored data. The location accuracy achieved by the intelligent locator is comparable to that obtained by the conventional triangulation method, while the applicability of the intelligent locator is more general since analysis of sonic ray paths is avoided. This is a promising method for non-destructive testing of aircraft frame structures by the acoustic emission method.