Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Pu, Hefu; Cai, Chao; Hu, Menglan; Deng, Tianping; Zheng, Rong; Luo, Jun

doi:10.3390/s21020532

Cited by 14 publications

(3 citation statements)

References 29 publications

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“…The microphone array is used as the receiving end to locate the direction of the acoustic source. The structure of microphone arrays [27][28][29][30][31][32] can be classified into linear arrays and planar arrays. In this study, the planar array was used.…”

Section: Introductionmentioning

confidence: 99%

Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

2022

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Sound signals have been widely applied in various fields. One of the popular applications is sound localization, where the location and direction of a sound source are determined by analyzing the sound signal. In this study, two microphone linear arrays were used to locate the sound source in an indoor environment. The TDOA is also designed to deal with the problem of delay in the reception of sound signals from two microphone arrays by using the generalized cross-correlation algorithm to calculate the TDOA. The proposed microphone array system with the algorithm can successfully estimate the sound source’s location. The test was performed in a standardized chamber. This experiment used two microphone arrays, each with two microphones. The experimental results prove that the proposed method can detect the sound source and obtain good performance with a position error of about 2.0~2.3 cm and angle error of about 0.74 degrees. Therefore, the experimental results demonstrate the feasibility of the system.

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Section: Introductionmentioning

confidence: 99%

Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

2022

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“…Moreover, the environmental sound recorded using two microphones is similar to the auditory scenes perceived through human ears. Therefore, the DUET has been adopted in a wide range of applications, including automation field [13]- [15] and smart living [16], [17].。 Ideally, the DUET requires the W-disjoint orthogonality (W-DO) of sound sources in the TF domain, meaning that all the sound must belong to only one source at any TF point. Consequently, the sound sources have a considerably sparse distribution and exhibit nearly no overlaps at any TF point.…”

Section: Introductionmentioning

confidence: 99%

Unique Methods for Determining the Attenuation and Delay in Blind Source Separation Based on the Degenerate Unmixing Estimation Technique

Lian

Lin

2021

IEEE Access

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The degenerate unmixing estimation technique (DUET), enables facile sound source separation through two signal mixtures. However, in numerous practical situations, identifying peaks in DUET histograms is difficult, which in turn prevents effective source separation. Specifically, sound sources with short time percentages in mixtures are more unlikely to form peaks in a histogram. Besides, when the noise floor of mixtures is high, the height of the histogram peak may be reduced, which causes peak position bias and prevents effective source separation. In this study, unique methods are proposed to solve the aforementioned problems. A subhistogram is established for each time frame; thus, the original histogram is divided into a series of subhistograms. Two measurement indices are then proposed to identify the accurate attenuation and delay parameters for sound sources: maximum distribution, which is based on the infinity norm, and variance distribution, which is based on variances. The results verify that maximum distribution effectively highlights the peaks of instantaneous sound sources when the time percentage difference between sound sources is excessively high. In this scenario, the conventional histogram is unable to find the peaks. When a strong noise disturbance is present in mixtures, variance distribution can be employed to estimate peak positions with lower biases than those in the conventional histogram. In addition to more well-defined and intense peaks, the proposed method can also reduce the bias error by 71% when the SNR is 0 dB. Variance distribution is more robust against noise disturbance compared to conventional histograms and can be adopted in a wide range of applications.INDEX TERMS Attenuation and delay histogram, Blind source separation, DUET, Instantaneous sound sources, W-disjoint orthogonality.

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“…Due to the characteristics of the BSS algorithm, it can quickly and correctly process the integrated signal in the time-varying case. In the field of radar, the BSS algorithm has been applied to the design of split-beam integrated signals for radar, and the corresponding processing [20]. At present, few people have considered whether the occurrence of communication errors in ISUAC signals affects the detection performance of the system and whether the signal processing affects the detection signal detection probability, which is the focus of this paper.…”

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confidence: 99%

Waveform design and signal processing method for integrated underwater detection and communication system

Niu

Zhang

Shi

2022

IET Radar Sonar & Navi

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For the integrated system of underwater detection and communication, an emitted waveform should satisfy both detection and communication requirements. The signal processing method at the receiving end must also accomplish target detection and communication accordingly. This study uses a generalised sinusoidal frequency modulated (GSFM) waveform with a carrier to ensure detection performance. At the same time, the communication information encoding with Gaussian Minimum Shift Keying is modulated to the GSFM signal for communication purposes. Unlike previous work, an improved Blind Source Separation algorithm is utilised at the receiving end, which is better adapted to waveform separation and processing in the underwater time-varying unknown environment. The analysis of detection probability, peak-to-average ratio, and signal processing results show that the proposed waveform and corresponding signal processing scheme can effectively meet the need for integrated underwater detection and communication system. K E Y W O R D S acoustic signal detection, acoustic signal processing 1 | INTRODUCTION This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Cited by 14 publications

References 29 publications

Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

Unique Methods for Determining the Attenuation and Delay in Blind Source Separation Based on the Degenerate Unmixing Estimation Technique

Waveform design and signal processing method for integrated underwater detection and communication system

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