Acoustic Camera Design with Different Types of MEMS Microphone Arrays

Grubeša, Sanja; Stamać, Jasna; Suhanek, Mia

doi:10.11648/j.ajese.20190304.14

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…Stoga je za potrebe projekta ERDF KK.01.2.1.01.0103 4D Akustička kamera razvijen prototip akustičke kamere, prikazan na slici 2. Razvoj same kamere detaljno je opisan u člancima autora (Stamać et al, 2019., Grubeša et al, 2019.…”

Section: Načelo Rada Akustičke Kamereunclassified

Akustička rješenja za detekciju dronova s ciljem povećanja opće sigurnosti

Grubeša¹,

Suhanek²,

Petošić³

et al. 2020

Sigurnost (Online)

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U današnje doba male bespilotne letjelice postaju sve popularnije. Postoje njihove razne inačice, ali po svojoj popularnosti prednjače kvadrokopteri odnosno dronovi. Primjenu nalaze većinom u komercijalnim svrhama ili kao nečiji hobi, međutim mogu biti korišteni i u ilegalne svrhe poput krijumčarenja ili prijenosa eksploziva. Veliki problem predstavljaju i ako se koriste na točno određenim lokacijama poput zračnih luka. Dronove je iznimno teško detektirati zbog njihovih relativno malenih dimenzija, prednjeg dijela napravljenog od plastike te električnih motora koji emitiraju vrlo male količine toplinske energije. U tom smislu konvencionalni radari ili infracrvene kamere jednostavno nisu dovoljne u detekciji dronova. Cilj istraživanja opisanog u ovom članku je ustanoviti koje su mogućnosti akustičkog rješenja za detekciju dronova, odnosno utvrditi zvučne razine malih UAV letjelica i na temelju te zvučne razine odrediti koja je teoretska granica udaljenosti na kojoj je moguće akustički detektirati dron. Također je istraženo koliko ta udaljenost raste ako se kao akustički detektor koristi akustička kamera. Očekuje se da će ishodi ovog istraživanja poboljšati opću sigurnost jer optimiziraju nekoliko vrsta pristupa u svrhu bolje detekcije dronova.

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Section: Načelo Rada Akustičke Kamereunclassified

Akustička rješenja za detekciju dronova s ciljem povećanja opće sigurnosti

Grubeša¹,

Suhanek²,

Petošić³

et al. 2020

Sigurnost (Online)

Self Cite

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“…However, small distances between sensors in these cameras lead to small time differences of the arriving sound signals, which reduce the localization performance for low-frequency sounds. Due to the correspondingly large wavelength for low-frequency sounds, sufficiently large sensor distances are required which in principle increases the size of acoustic cameras [14]. Furthermore, an important factor in sound source localization is the number of microphones.…”

Section: Introductionmentioning

confidence: 99%

Direction-of-arrival estimation for acoustic signals based on direction-dependent parameter tuning of a bioinspired binaural coupling system

2023

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Bioinspired methods for sound source localization offer opportunities for resource reduction as well as concurrent performance improvement in contrast to conventional techniques. Usually, sound source localization requires a large number of microphones arranged in irregular geometries, and thus has high resource requirements in terms of space and data processing. Motivated by biology and using digital signal processing methods, an approach that adapts the coupled hearing system of the fly Ormia ochracea with a minimally distant two-microphone array is presented. Despite its physiology, the fly is able to overcome physical limitations in localizing low-frequency sound sources. By exploiting the filtering effect of the coupling system, the direction-of-arrival (DOA) of the sound is determined with two microphones at an intermediate distance of 0,06m. For conventional beamforming algorithms, these physical limitations would result in degraded localization performance. In this work, the bioinspired coupling system is analyzed and subsequently parameterized direction-sensitive for different directions of incidence of the sound. For the parameterization, an optimization method is presented which can be adopted for excitation with plane as well as spherical sound wave propagation. Finally, the method was assessed using simulated and measured data. For 90% of the simulated scenarios, the correct direction of incidence could be determined with an accuracy of less than 1° despite the use of a minimal distant two-microphone array. The experiments with measured data also resulted in a correct determination of the direction of incidence, which qualifies the bioinspired method for practical use in digital hardware system.

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“…Increasing the frequency at which the acoustic camera design was accomplished, increases the cutoff frequency, i.e., the maximum frequency for which the camera can be used [19]. In our previous research [19,20], several simulations were performed considering square, circular and hemisphere-shaped MEMS arrays with varying numbers of microphones and varying spacing between the microphones. Since the directivity pattern of a microphone array is frequency dependent [21], simulations were performed in the frequency band from 63 Hz to 8 kHz, though the results are presented only for three frequencies of interest, i.e., 1 kHz, 2 kHz and 4 kHz.…”

Section: Introductionmentioning

confidence: 99%

Use of Genetic Algorithms for Design an FPGA-Integrated Acoustic Camera

Grubeša

Stamać²,

Suhanek

et al. 2022

Sensors

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The goal of this paper is to design a broadband acoustic camera using micro-electromechanical system (MEMS) microphones. The paper describes how an optimization of the microphone array has been carried out. Furthermore, the final goal of the described optimization is that the gain in the desired direction and the attenuation of side lobes is maximized at a frequency up to 4 kHz. Throughout the research, various shapes of microphone arrays and their directivity patterns have been considered and analyzed using newly developed algorithms implemented in Matlab. A hemisphere algorithm, genetic algorithm, and genetic square algorithm were used to find the optimal position and number of microphones placed on an acoustic camera. The proposed acoustic camera design uses a large number of microphones for high directional selectivity, while a field programmable gate array system on a chip (FPGA SoC) is selected as the processing element of the system. According to the obtained results, three different acoustic camera prototypes were developed. This paper presents simulations of their characteristics, compares the obtained measurements, and discusses the positive and negative sides of each acoustic camera prototype.

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Acoustic Camera Design with Different Types of MEMS Microphone Arrays

Cited by 5 publications

References 8 publications

Akustička rješenja za detekciju dronova s ciljem povećanja opće sigurnosti

Akustička rješenja za detekciju dronova s ciljem povećanja opće sigurnosti

Direction-of-arrival estimation for acoustic signals based on direction-dependent parameter tuning of a bioinspired binaural coupling system

Use of Genetic Algorithms for Design an FPGA-Integrated Acoustic Camera

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