Underwater Sound Source Localization by EMD-Based Maximum Likelihood Method

B, Marxim Rahula Bharathi; Mohanty, Amiya Ranjan

doi:10.1007/s40857-018-0129-8

Cited by 19 publications

(6 citation statements)

References 28 publications

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“…For multiple sound sources, the localization algorithms are divided into two categories: one is the super-resolution spectrum estimation; the other is the beamforming. Over the past few decades, many 2D localization algorithms, such as multiple signal classification (MUSIC), 2 estimating signal parameter via rotational invariance techniques (ESPRIT), 3 maximum likelihood estimation (ML) 4 and various beamforming methods (BF), have been proposed for direction-of-arrival (DOA) estimation. The traditional algorithms are based on the far-field assumption that a signal travels as a plane wave and the difference in the amplitude attenuation of the received signal is ignored.…”

Section: Introductionmentioning

confidence: 99%

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

Yang

Sun

Guo

et al. 2022

International Journal of Aeroacoustics

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To improve the computation and real-time performances of the multiple signal classification (MUSIC) algorithm in 3D space, a fast sound source localization method based on the bat algorithm (BA) and the 3D-MUSIC, called BA-based 3D-MUSIC algorithm (3D-BMUSIC), is presented in this paper. 3D-BMUSIC greatly reduces the computation load by replacing the regular grid search with the BA. First, the near-field spherical wave model is established to obtain the spectral function of the 3D-MUSIC. Then, the spectral function is defined as the fitness function, which calculates the fitness value corresponding to each bat position. Finally, the global optimal bat position with the largest fitness value, as sound source localization, is obtained by successive iteration and sorting. The simulation and experiment show that 3D-BMUSIC accurately estimates the DOA and distance of near-field sources, and the root-mean-square error (RMSE) of 3D-BMUSIC is less than that of 3D-MUSIC. In addition, 3D-BMUSIC effectively reduces the computation time by approximately 96–98%. With shorter computation time and higher efficiency, 3D-BMUSIC promotes hardware implementation and is more suitable for high-precision localization of near-field sound sources.

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Section: Introductionmentioning

confidence: 99%

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

Yang

Sun

Guo

et al. 2022

International Journal of Aeroacoustics

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show abstract

“…Underwater source localization is a hot topic of current research, and it has been widely used in signal processing [1,2], sensor networks [3][4][5][6][7][8] and sonar systems [9][10][11][12]. Underwater source localization is a passive localization problem, that is, localization using the radiation information of the source signal.…”

Section: Introductionmentioning

confidence: 99%

Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm

2021

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In order to achieve precise localization in the underwater environment, an underwater localization method based on hybrid invasive weed algorithm is proposed. First, considering the insufficient local search capability of the invasive weed algorithm, the salp swarm algorithm is used to pre‐process the initial population, the position and velocity update formulas are employed to further improve the search depth, and the hybrid invasive weed algorithm is obtained. Then, the localization error is designed as the objective function to obtain the initial value of the source, and a new localization model is built using the initial values and interference parameters. Finally, an improved two‐step weighted least square method is used to obtain the precise location of the source. The performance of the algorithm is also verified by comparisons with Cramer‐Rao Lower Bound. Simulation experiments show that the proposed algorithm has better localization accuracy than other classic methods.

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“…Compared with other detection technology [5,6], SSL has a stronger anti-interference and higher concealment, thanks to its passive localization features and its flexible adoption of different microphone-array models, and algorithms for different target sound resources [7]. SSL has been widely employed in sonar [8], torpedos [9], underwater acoustic localization [10], underwater gliders [11] and other platforms [12,13]. It is worth mentioning that computer vision is the most popular method used nowadays for mobile robots to 'sense' and 'perceive' the environment and to identify its position in a GPS-denied environment.…”

Section: Introductionmentioning

confidence: 99%

A data complementary method for sound source localization based on four-element microphone array groups

Yang¹,

Xing²,

Yan³

2021

Meas. Sci. Technol.

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Data loss or distortion has adverse effects on sound source localization (SSL) accuracy and stability. Based on the sound source azimuth estimation algorithm, this paper establishes a model of a single four-element main microphone array, and proposes a data complementary method of SSL. The calculation formula of sound source coordinates is derived from the main array. Then, the effectiveness of the proposed algorithm is verified by the study of array parameters. Besides the sound velocity and elevation angle, the array parameters also include the distance between two array elements. Array groups are established surrounding the main array on the horizontal plane, through which the localization data are collected and complementarily processed, so as to relocate the sound source. The results show that the coordinate error rate against the theoretical data is approximately 5% and the error rate of the angle is approximately 0.5%. The SSL efficiency is well guaranteed.

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Underwater Sound Source Localization by EMD-Based Maximum Likelihood Method

Cited by 19 publications

References 28 publications

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm

A data complementary method for sound source localization based on four-element microphone array groups

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