SuperSoundcompass: a high-accuracy acoustic localization sensor using a small aperture microphone array

Li, Lei; Wang, Linfeng; Dong, Jie; Fu, Jintao; Gao, Yang; Qiao, Yiting; Zhu, Mingfu

doi:10.1088/1361-6501/ac0009

Cited by 9 publications

(6 citation statements)

References 55 publications

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“…Its popularity in various industries and acoustic research has spawned several variants of arrays for the detection of sound emission. Many versions are large and have a large number of sensors, which makes them unsuitable for continuous measurements, [53][54][55][56][57][58][59], especially in the low frequency range, [60][61][62][63][64][65][66][67][68]. Microphone arrays for environmental noise measurements are more or less limited to single use cases and for the purpose of increasing SNR by forming a synthesized signal from all microphones, [53][54][55][69][70][71][72][73][74][75][76][77].…”

Section: Source Localizationmentioning

confidence: 99%

Automated identification and assessment of environmental noise sources

Murovec

Čurović

Železnik

et al. 2023

Heliyon

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Section: Source Localizationmentioning

confidence: 99%

Automated identification and assessment of environmental noise sources

Murovec

Čurović

Železnik

et al. 2023

Heliyon

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Section: Sound Source Localization Methods Based On Msc Algorithmmentioning

confidence: 97%

“…The array sensor and the corresponding coordinate definition method used in this paper are shown in Figure 2. According to the research (L. Li et al, 2021), in the same case, the smaller the radius of the circular array, the better the sound source positioning effect. Therefore, the five sensors in the innermost circle of the array sensor are used for spectrum estimation to determine the speed and position of the walking part, and then determine the time series.…”

Section: Determination Of the Position And Speed Of The Walking Part ...mentioning

confidence: 97%

Research on fault diagnosis of bearings in walking part of wall‐building robot based on roadside acoustic signal

Gao

Zhang

et al. 2022

Journal of Field Robotics

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The walking part of the wall‐building robot is an important component whose health influences the robot's overall performance, and the bearing of the walking part is a critical but often disregarded component. As a result, based on acoustic signals from the roadside, this study proposes a method of bearing fault monitoring of walking parts to ensure the more stable operation of the wall‐building robot. To begin, due to the Doppler effect caused by the relative displacement between the sensor and the walking part, the collected acoustic signal has frequency shift and amplitude attenuation, so the multiple signal classification spectrum estimation method with added windows is first used to determine the position and speed of the walking part bearing in real time, and then obtain a resampled time series of the distorted signal. Second, the distorted signal is resampled by Morse acoustic theory to correct the distorted sound signal collected by the array sensor. Third, a multitask deep learning method with an attention mechanism is designed to jointly diagnose the fault type and damage degree of bearing by analyzing the corrected acoustic signal. The experimental results show that the method can effectively restore the distorted signal while still accurately and stably detecting the fault type and damage degree of the bearing under a variety of working conditions and external disturbances, making it more suitable for the work of wall‐building robots.

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“…Sensor arrays have been widely used in radar [1], sonar [2], remote sensing [3] and other systems [4,5], due to the significant advantages in terms of implementation cost and hardware complexity. Recently, the wideband beamforming capability has become an important indicator for sparse array design [6].…”

Section: Introductionmentioning

confidence: 99%

Sparse hydrophone array synthesis for frequency‐invariant and multi‐angle beampatterns using block‐structured Bayesian compressive sensing

Wang

Zhao

2023

IET Radar Sonar & Navi

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To solve the synthesised accuracy degradation of traditional Bayesian compressive sensing (BCS) in wideband multi‐beam hydrophone array synthesis, a novel sparse array synthesis method based on block‐structure Bayesian compressive sensing (BS‐BCS) is proposed for frequency‐invariant and multi‐angle beampatterns. The multi‐angle beampatterns at different frequencies are synthesised in block structure using the shared position strategy which effectively reduces the number of array elements. In order to meet the minimum spacing requirement of adjacent array elements in practical engineering, the constraint converted off‐grid method is proposed to improve the array synthesis accuracy. The grid scaling is introduced to obtain the possible array element positions. The array positions and weights can be solved by the BCS solver and corrected by Taylor perturbation. To validate the effectiveness and feasibility of the proposed method, simulations and actual experiments are carried out. The synthesised errors and peak sidelobe levels (PSLLs) of multi‐angle beampatterns obtained by the constraint converted off‐grid method outperforms those of other methods. The beamforming results of actual experiments in marine environment show that the PSLLs of the beampatterns obtained by BS‐BCS is lower at least 6.3 dB than that of uniform array, which demonstrates the effectiveness of the proposed method.

show abstract

SuperSoundcompass: a high-accuracy acoustic localization sensor using a small aperture microphone array

Cited by 9 publications

References 55 publications

Automated identification and assessment of environmental noise sources

Automated identification and assessment of environmental noise sources

Research on fault diagnosis of bearings in walking part of wall‐building robot based on roadside acoustic signal

Sparse hydrophone array synthesis for frequency‐invariant and multi‐angle beampatterns using block‐structured Bayesian compressive sensing

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