scholarly journals Localization of Two Sound Sources Based on Compressed Matched Field Processing with a Short Hydrophone Array in the Deep Ocean

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3810 ◽  
Author(s):  
Ran Cao ◽  
Kunde Yang ◽  
Qiulong Yang ◽  
Peng Chen ◽  
Quan Sun ◽  
...  
Keyword(s):  
Greedy Algorithm ◽  
Source Localization ◽  
Signal To Noise Ratio ◽  
Deep Ocean ◽  
Spatial Filter ◽  
Sound Sources ◽  
Matched Field Processing ◽  
Array Aperture ◽  
Hydrophone Array ◽  
The Greedy Algorithm

Passive multiple sound source localization is a challenging problem in underwater acoustics, especially for a short hydrophone array in the deep ocean. Several attempts have been made to solve this problem by applying compressive sensing (CS) techniques. In this study, one greedy algorithm in CS theory combined with a spatial filter was developed and applied to a two-source localization scenario in the deep ocean. This method facilitates localization by utilizing the greedy algorithm with a spatial filter at several iterative loops. The simulated and experimental data suggest that the proposed method provides a certain localization performance improvement over the use of the Bartlett processor and the greedy algorithm without a spatial filter. Additionally, the effects on the source localization caused by factors such as the array aperture, number of hydrophones or snapshots, and signal-to-noise ratio (SNR) are demonstrated.

scholarly journals Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 532
Author(s):  
Henglin Pu ◽  
Chao Cai ◽  
Menglan Hu ◽  
Tianping Deng ◽  
Rong Zheng ◽  
...  
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Indoor Localization ◽  
Weighting Function ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
Sound Source Localization ◽  
Angle Of Arrival ◽  
Sound Sources ◽  
Localization Algorithms

Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.

A BOUNDARY INTEGRAL METHOD FOR ACOUSTIC SOURCE LOCALIZATION IN A WAVEGUIDE WITH INCLUSIONS

1994 ◽  
Vol 02 (02) ◽  
pp. 133-145 ◽  
Author(s):  
YONGZHI XU ◽  
YI YAN
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Boundary Integral ◽  
Boundary Integral Method ◽  
Rigid Boundary ◽  
Matched Field Processing ◽  
Acoustic Source Localization ◽  
Continuous Waves ◽  
Hydrophone Array ◽  
Computation Load

In this paper, we continue our study on combining the matched field processing with the boundary integral equation (BIE) method of scattering theory to solve a sound source localization problem in a shallow ocean with a large inclusion which has a rigid boundary. We consider an enviroment where continuous waves (CW) are produced by a sound source, scattered by the inclusion, and then received by a hydrophone array. The symmetry of the waveguide is destroyed by the existence of the inclusion, and a proper procedure is therefore required to avoid the mismatching. We present a numerical scheme which makes use of the separation of the source and the detection array, and a BIE method. The separation greatly reduces the computation load. The BIE method preserves a certain accuracy on one hand and minimizes arithmetic operations on the other. Some numerical simulations using this scheme are presented.

Influence of Different Impulse Response Measurement Signals on MUSIC-Based Sound Source Localization

2017 ◽  
Vol 29 (1) ◽  
pp. 72-82 ◽  
Author(s):  
Takuya Suzuki ◽  
◽  
Hiroaki Otsuka ◽  
Wataru Akahori ◽  
Yoshiaki Bando ◽  
...  
Keyword(s):  
Impulse Response ◽  
Source Localization ◽  
Sound Source ◽  
Transfer Functions ◽  
Signal To Noise Ratio ◽  
Microphone Array ◽  
Sound Source Localization ◽  
Sound Sources ◽  
Response Measurement ◽  
Significant Difference

[abstFig src='/00290001/07.jpg' width='300' text='Six impulse response measurement signals' ] Two major functions, sound source localization and sound source separation, provided by robot audition open source software HARK exploit the acoustic transfer functions of a microphone array to improve the performance. The acoustic transfer functions are calculated from the measured acoustic impulse response. In the measurement, special signals such as Time Stretched Pulse (TSP) are used to improve the signal-to-noise ratio of the measurement signals. Recent studies have identified the importance of selecting a measurement signal according to the applications. In this paper, we investigate how six measurement signals – up-TSP, down-TSP, M-Series, Log-SS, NW-SS, and MN-SS – influence the performance of the MUSIC-based sound source localization provided by HARK. Experiments with simulated sounds, up to three simultaneous sound sources, demonstrate no significant difference among the six measurement signals in the MUSIC-based sound source localization.

SOUND SOURCE LOCALIZATION IN THREE-DIMENSIONAL SPACE IN REAL TIME WITH REDUNDANCY CHECKS

2012 ◽  
Vol 20 (01) ◽  
pp. 1250007 ◽  
Author(s):  
NA ZHU ◽  
SEAN F. WU
Keyword(s):  
Source Localization ◽  
Signal To Noise Ratio ◽  
Dimensional Space ◽  
Broad Band ◽  
Three Dimensional ◽  
Sound Sources ◽  
Detection Range ◽  
Basic Model ◽  
Improved Model ◽  
Three Dimensional Space

Triangulation is commonly used for source localization and most triangulation applications are based on intersection of the bearing direction to locate a source on a two-dimensional plane. In this paper, two new mathematical models (a basic model and an improved one) that expands the traditional triangulation concept to three-dimensional space are developed to locate multiple incoherent sound sources. The basic model uses four microphones and concentrates on solving a set of three quadratic equations simultaneously. The improved model requires more than four microphones and uses the solution from the basic model, as well as analyzing the intersection of bearing angles. Redundancy checks on the time differences of arrival are added to further reduce the source localization error in the improved model. Moreover, the input data are pre-processed and de-noised through filtering and windowing to enhance the effective signal to noise ratio. Various sound sources are tested, including transient, impulsive, continuous, broad-band, and narrow-band sounds. Numerical simulations and experimental validation using the real world sound sources are conducted. The impacts of the source direction/source detection range on the accuracy of source localization results are examined and discussed.

scholarly journals Spherical Reverse Beamforming for Sound Source Localization Based on the Inverse Method

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2618 ◽  
Author(s):  
Chao Sun ◽  
Yuechan Liu
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Background Noise ◽  
Inverse Method ◽  
Optimization Problem ◽  
Sound Field ◽  
Sound Source Localization ◽  
Sound Sources ◽  
Sound Field Reconstruction ◽  
Array Aperture

A spherical array is not limited to providing an acoustic map in all directions by the azimuth of the array. In this paper, spherical reverse beamforming for sound source localization based on spherical harmonic beamforming and the principle of sound field reconstruction is proposed in order to output a sharper scanning beam. It is assumed that there is an imaginary sound source at each scan point, and the acoustic map of a spherical array to the actual sound source is regarded as the combination of all of the imaginary sound sources. Sound source localization can be realized by calculating the contribution of each imaginary sound source to the sound field. Also in this work, the non-convex constrained optimization problem is established using p-norm. Combined with the norm method, the sparse solution of the imaginary sources is obtained through iterative weighted techniques, and the resolution of sound source localization is improved significantly. The performance of this method is investigated in comparison to conventional spherical beamforming. The numerical results show that the proposed method can achieve higher resolution for the localization of sound sources without being limited by the frequency and array aperture, and has a stronger ability to suppress fluctuations in background noise.

Implementasi Algoritma Dijkstra Pada Game Pacman

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 170-176
Author(s):  
Anggit Dwi Hartanto ◽  
Aji Surya Mandala ◽  
Dimas Rio P.L. ◽  
Sidiq Aminudin ◽  
Andika Yudirianto
Keyword(s):  
Artificial Intelligence ◽  
Greedy Algorithm ◽  
Dijkstra Algorithm ◽  
Testing Phase ◽  
A Value ◽  
Route Problem ◽  
Starting Point ◽  
The Greedy Algorithm

Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

scholarly journals An Optimized Algorithm and Test Bed for Improvement of Efficiency of ESS and Energy Use

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 388 ◽  
Author(s):  
Seung-Mo Je ◽  
Jun-Ho Huh
Keyword(s):  
Greedy Algorithm ◽  
Energy Use ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Test Bed ◽  
C Language ◽  
Improvement Plan ◽  
The Republic ◽  
The Greedy Algorithm

The Republic of Korea (ROK) has four distinct seasons. Such an environment provides many benefits, but also brings some major problems when using new and renewable energies. The rainy season or typhoons in summer become the main causes of inconsistent production rates of these energies, and this would become a fatal weakness in supplying stable power to the industries running continuously, such as the aquaculture industry. This study proposed an improvement plan for the efficiency of Energy Storage System (ESS) and energy use. Use of sodium-ion batteries is suggested to overcome the disadvantages of lithium-ion batteries, which are dominant in the current market; a greedy algorithm and the Floyd–Warshall algorithm were also proposed as a method of scheduling energy use considering the elements that could affect communication output and energy use. Some significant correlations between communication output and energy efficiency have been identified through the OPNET-based simulations. The simulation results showed that the greedy algorithm was more efficient. This algorithm was then implemented with C-language to apply it to the Test Bed developed in the previous study. The results of the Test Bed experiment supported the proposals.

scholarly journals Acoustic source localization using the open spherical microphone array in the low-frequency range

2019 ◽  
Vol 283 ◽  
pp. 04001
Author(s):  
Boquan Yang ◽  
Shengguo Shi ◽  
Desen Yang
Keyword(s):  
Source Localization ◽  
Generalized Inverse ◽  
Microphone Array ◽  
Low Frequency ◽  
Poor Performance ◽  
Microphone Arrays ◽  
Three Dimension ◽  
Frequency Range ◽  
Array Aperture ◽  
Regularization Matrix

Recently, spherical microphone arrays (SMA) have become increasingly significant for source localization and identification in three dimension due to its spherical symmetry. However, conventional Spherical Harmonic Beamforming (SHB) based on SMA has limitations, such as poor resolution and high side-lobe levels in image maps. To overcome these limitations, this paper employs the iterative generalized inverse beamforming algorithm with a virtual extrapolated open spherical microphone array. The sidelobes can be suppressed and the main-lobe can be narrowed by introducing the two iteration processes into the generalized inverse beamforming (GIB) algorithm. The instability caused by uncertainties in actual measurements, such as measurement noise and configuration problems in the process of GIB, can be minimized by iteratively redefining the form of regularization matrix and the corresponding GIB localization results. In addition, the poor performance of microphone arrays in the low-frequency range due to the array aperture can be improved by using a virtual extrapolated open spherical array (EA), which has a larger array aperture. The virtual array is obtained by a kind of data preprocessing method through the regularization matrix algorithm. Both results from simulations and experiments show the feasibility and accuracy of the method.

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