SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field

Shooter localization and weapon classification with soldier-wearable networked sensors

The paper presents a wireless sensor network-based mobile countersniper system. A sensor node consists of a helmetmounted microphone array, a COTS MICAz mote for internode communication and a custom sensorboard that implements the acoustic detection and Time of Arrival (ToA) estimation algorithms on an FPGA. A 3-axis compass provides self orientation and Bluetooth is used for communication with the soldier’s PDA running the data fusion and the user interface. The heterogeneous sensor fusion algorithm can work with data from a single sensor or it can fuse ToA or Angle of Arrival (AoA) observations of muzzle blasts and ballistic shockwaves from multiple sensors. The system estimates the trajectory, the range, the caliber and the weapon type. The paper presents the system design and the results from an independent evaluation at the US Army Aberdeen Test Center. The system performance is characterized by 1-degree trajectory precision and over 95 % caliber estimation accuracy for all shots, and close to 100 % weapon estimation accuracy for 4 out of 6 guns tested

Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

International audienc

Design Considerations When Accelerating an FPGA-Based Digital Microphone Array for Sound-Source Localization

The use of microphone arrays for sound-source localization is a well-researched topic. The response of such sensor arrays is dependent on the quantity of microphones operating on the array. A higher number of microphones, however, increase the computational demand, making real-time response challenging. In this paper, we present a Filter-and-Sum based architecture and several acceleration techniques to provide accurate sound-source localization in real-time. Experiments demonstrate how an accurate sound-source localization is obtained in a couple of milliseconds, independently of the number of microphones. Finally, we also propose different strategies to further accelerate the sound-source localization while offering increased angular resolution

Acceleration Techniques for Sparse Recovery Based Plane-wave Decomposition of a Sound Field

Plane-wave decomposition by sparse recovery is a reliable and accurate technique for plane-wave decomposition which can be used for source localization, beamforming, etc. In this work, we introduce techniques to accelerate the plane-wave decomposition by sparse recovery. The method consists of two main algorithms which are spherical Fourier transformation (SFT) and sparse recovery. Comparing the two algorithms, the sparse recovery is the most computationally intensive. We implement the SFT on an FPGA and the sparse recovery on a multithreaded computing platform. Then the multithreaded computing platform could be fully utilized for the sparse recovery. On the other hand, implementing the SFT on an FPGA helps to flexibly integrate the microphones and improve the portability of the microphone array. For implementing the SFT on an FPGA, we develop a scalable FPGA design model that enables the quick design of the SFT architecture on FPGAs. The model considers the number of microphones, the number of SFT channels and the cost of the FPGA and provides the design of a resource optimized and cost-effective FPGA architecture as the output. Then we investigate the performance of the sparse recovery algorithm executed on various multithreaded computing platforms (i.e., chip-multiprocessor, multiprocessor, GPU, manycore). Finally, we investigate the influence of modifying the dictionary size on the computational performance and the accuracy of the sparse recovery algorithms. We introduce novel sparse-recovery techniques which use non-uniform dictionaries to improve the performance of the sparse recovery on a parallel architecture

Development and Human Factors Evaluation of a Portable Auditory Localization Acclimation Training System

Auditory situation awareness (ASA) is essential for safety and survivability in military operations where many of the hazards are not immediately visible. Unfortunately, the Hearing Protection Devices (HPDs) required to operate in these environments can impede auditory localization performance. Promisingly, recent studies have exhibited the plasticity of the human auditory system by demonstrating that training can improve auditory localization ability while wearing HPDs, including military Tactical Communications and Protective Systems (TCAPS). As a result, the U.S. military identified the need for a portable system capable of imparting auditory localization acquisition skills at similar levels to those demonstrated in laboratory environments. The purpose of this investigation was to develop and validate a Portable Auditory Localization Acclimation Training (PALAT) system equipped with an improved training protocol against a proven laboratory grade system referred to as the DRILCOM system and subsequently evaluate the transfer-of-training benefit in a field environment. In Phase I, a systems decision process was used to develop a prototype PALAT system consisting of an expandable frame housing 32-loudspeakers operated by a user-controlled tablet computer capable of reproducing acoustically accurate localization cues similar to the DRILCOM system. Phase II used a within-subjects human factors experiment to validate whether the PALAT system could impart similar auditory localization training benefits as the DRILCOM system. Results showed no significant difference between the two localization training systems at each stage of training or in training rates for the open ear and with two TCAPS devices. The PALAT system also demonstrated the ability to detect differences in localization accuracy between listening conditions in the same manner as the DRILCOM system. Participant ratings indicated no perceived difference in localization training benefit but significantly preferred the PALAT system user interface which was specifically designed to improve usability features to meet requirements of a user operable system. The Phase III investigation evaluated the transfer-of-training benefit imparted by the PALAT system using a broadband stimulus to a field environment using gunshot stimulus. Training under the open ear and in-the-ear TCAPS resulted in significant differences between the trained and untrained groups from in-office pretest to in-field posttest

Development and Human Factors Evaluation of a Portable Auditory Localization Acclimation Training System

Auditory situation awareness (ASA) is essential for safety and survivability in military operations where many of the hazards are not immediately visible. Unfortunately, the Hearing Protection Devices (HPDs) required to operate in these environments can impede auditory localization performance. Promisingly, recent studies have exhibited the plasticity of the human auditory system by demonstrating that training can improve auditory localization ability while wearing HPDs, including military Tactical Communications and Protective Systems (TCAPS). As a result, the U.S. military identified the need for a portable system capable of imparting auditory localization acquisition skills at similar levels to those demonstrated in laboratory environments. The purpose of this investigation was to develop and validate a Portable Auditory Localization Acclimation Training (PALAT) system equipped with an improved training protocol against a proven laboratory grade system referred to as the DRILCOM system and subsequently evaluate the transfer-of-training benefit in a field environment. In Phase I, a systems decision process was used to develop a prototype PALAT system consisting of an expandable frame housing 32-loudspeakers operated by a user-controlled tablet computer capable of reproducing acoustically accurate localization cues similar to the DRILCOM system. Phase II used a within-subjects human factors experiment to validate whether the PALAT system could impart similar auditory localization training benefits as the DRILCOM system. Results showed no significant difference between the two localization training systems at each stage of training or in training rates for the open ear and with two TCAPS devices. The PALAT system also demonstrated the ability to detect differences in localization accuracy between listening conditions in the same manner as the DRILCOM system. Participant ratings indicated no perceived difference in localization training benefit but significantly preferred the PALAT system user interface which was specifically designed to improve usability features to meet requirements of a user operable system. The Phase III investigation evaluated the transfer-of-training benefit imparted by the PALAT system using a broadband stimulus to a field environment using gunshot stimulus. Training under the open ear and in-the-ear TCAPS resulted in significant differences between the trained and untrained groups from in-office pretest to in-field posttest

Development and Human Factors Evaluation of a Portable Auditory Localization Acclimation Training System

Auditory situation awareness (ASA) is essential for safety and survivability in military operations where many of the hazards are not immediately visible. Unfortunately, the Hearing Protection Devices (HPDs) required to operate in these environments can impede auditory localization performance. Promisingly, recent studies have exhibited the plasticity of the human auditory system by demonstrating that training can improve auditory localization ability while wearing HPDs, including military Tactical Communications and Protective Systems (TCAPS). As a result, the U.S. military identified the need for a portable system capable of imparting auditory localization acquisition skills at similar levels to those demonstrated in laboratory environments. The purpose of this investigation was to develop and validate a Portable Auditory Localization Acclimation Training (PALAT) system equipped with an improved training protocol against a proven laboratory grade system referred to as the DRILCOM system and subsequently evaluate the transfer-of-training benefit in a field environment. In Phase I, a systems decision process was used to develop a prototype PALAT system consisting of an expandable frame housing 32-loudspeakers operated by a user-controlled tablet computer capable of reproducing acoustically accurate localization cues similar to the DRILCOM system. Phase II used a within-subjects human factors experiment to validate whether the PALAT system could impart similar auditory localization training benefits as the DRILCOM system. Results showed no significant difference between the two localization training systems at each stage of training or in training rates for the open ear and with two TCAPS devices. The PALAT system also demonstrated the ability to detect differences in localization accuracy between listening conditions in the same manner as the DRILCOM system. Participant ratings indicated no perceived difference in localization training benefit but significantly preferred the PALAT system user interface which was specifically designed to improve usability features to meet requirements of a user operable system. The Phase III investigation evaluated the transfer-of-training benefit imparted by the PALAT system using a broadband stimulus to a field environment using gunshot stimulus. Training under the open ear and in-the-ear TCAPS resulted in significant differences between the trained and untrained groups from in-office pretest to in-field posttest

A Hardware Based Audio Event Detection System

Audio event detection and analysis is an important tool in many fields, from entertainment to security. Recognition technologies are used daily for parsing voice commands, tagging songs, and real time detection of crimes or other undesirable events. The system described in this work is a hardware based application of an audio detection system, implemented on an FPGA. It allows for the detection and characterization of gunshots and other events, such as breaking glass, by comparing a recorded audio sample to 20+ stored fingerprints in real time. Additionally, it has the ability to record flagged events and supports integration with mesh networks to send alerts