Acoustic Source Localization Based on Generalized Cross-correlation Time-delay Estimation

Chen, Lin; Liu, Yongchun; Kong, Fancheng; He, Na Na

doi:10.1016/j.proeng.2011.08.915

Cited by 57 publications

(23 citation statements)

References 2 publications

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“…Perez-Lorenzo et al [18] evaluate some GCC methods in typical conditions of real scenarios with the presence of external, stationary, and in most cases, correlated noise sources. Chen et al [19] analyze the performance of several weighting functions in TDOA algorithm based on GCC and indicate that PHAT weighting is the best choice for SSL using GCC method for its small fluctuations, sharp peak, and strong antijamming ability. Padoisa et al [20] develop an improved GCC method to detect the source positions.…”

Section: Related Workmentioning

confidence: 99%

“…The coordinates of the sound source can be obtained by using Newton iterative algorithm to solve (19). According to (19), four sets of equations and their corresponding solutions can be obtained. The paper takes the mean of the four solutions as the final results, which is the location of the sound source.…”

Section: The Localization Algorithm Based On Iterative Optimizationmentioning

confidence: 99%

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A Sound Source Localization Device Based on Rectangular Pyramid Structure for Mobile Robot

Chen

Yang

2019

Journal of Sensors

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A sound source localization device based on a multimicrophone array with the rectangular pyramid structure is proposed for mobile robot in some indoor applications. Firstly, a time delay estimation method based on the cross-power spectral phase algorithm and a fast search strategy of peak value based on the geometric distribution of microphones are developed to estimate the sound propagation delay differences between two microphones. Moreover, a rejection strategy is presented to evaluate the correctness of the delay difference values. And then, the device’s geometric equations based on the time-space mapping relationship are established to calculate the position of the sound source. For fast solving the equations, the multimicrophone array space is divided into several subspaces to narrow the solution range, and Newton iteration algorithm is introduced to solve the equations, while its solution is evaluated by an evaluation mechanism based on coordinate thresholds. Finally, some experiments are carried out to verify the performance of the device, of which the results show that the device can achieve sound source localization with a high accuracy.

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Section: Related Workmentioning

confidence: 99%

Section: The Localization Algorithm Based On Iterative Optimizationmentioning

confidence: 99%

A Sound Source Localization Device Based on Rectangular Pyramid Structure for Mobile Robot

Chen

Yang

2019

Journal of Sensors

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“…The Direction parameter respectively were ( ) ( ) 1 Fig.2 showed the signals of the speaker. We could know that the main speaker was the signal 1 s in signal space.…”

Section: Algorithmentioning

confidence: 99%

“…Now Sound source localization method based on microphone array can be divided into three categories: sound source localization technology based on cross-correlation time delay estimation [1], sound source localization technology based on steerable beam forming technology and space spectrum estimation. As there are multiple sound sources in a noisy environment, space spectrum estimation method can accurately estimates the direction of main speaker.…”

Section: Introductionmentioning

confidence: 99%

A design of algorithm based on microphone array

2014

2014 12th International Conference on Signal Processing (ICSP)

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To extract acoustical signal of the main speaker in noisy environment, a signal transmission model was established based on cross microphone array in this paper. According to the signal transmission model, the main speaker's direction was estimated by utilizing improved MUSIC, and then using a spatial filtering method to track and pick up the main speaker's voice through the microphone array. Experimental results show that it is feasible and reasonable to extract acoustical signal of the main speaker in noisy environment by using the novel method, and it is more accurately to estimate the direction of the desired signal. And after processed by the novel method, the desired signal' SNR is enhanced and the interference signals are well suppressed.

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“…Miles has examined the effect of signal coherence loss and noise correlation on its detection performance in the presence of frequency-dependent correlated noise fields [12]. The prewhitening techniques are often applied in the generalized cross correlation (GCC) function to improve the performance of time delay estimation [13], [14] in many fields [15]- [17]. The improvement on time delay estimation by the prefiltering techniques and beamforming in the split beam process has also been testified [1] [7].…”

Section: Introductionmentioning

confidence: 99%

Insight Into Split Beam Cross-Correlator Detector With the Prewhitening Technique

Chen

Zhang

et al. 2019

IEEE Access

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The split-beam processing methods have been widely used for the bearing estimation of broadband signals with a line array. They can achieve high bearing resolution at a cost of the reduced processing gain. The split beam cross-correlator detector (SBCD), one of these methods, is to obtain a cross-correlation series from the redundant two-dimensional cross correlations between beam pairs of two sub-arrays. When SBCD is combined with prewhitening techniques in generalized cross correlation (GCC), it shows some unique output characteristics beneficial for both bearing estimation and detection, such as the low output background, the power-independent output, the capacity of accentuating weak targets, suppressing strong interferences, and the resistance to grating lobes aliasing in the spatial spectrum. This paper is to reveal these characteristics and underneath reasons through theories and simulations. Experiment results with an array of 268.75m in South China Sea validate the present theories, and manifest that SBCD with the prewhitening technique can achieve improved performances on both the direction-of-arrival (DOA) estimation and detection of weak broadband targets. In terms of efficiency and robustness for real time applications, it shows great potential in actual underwater environment. INDEX TERMS Cross-correlator, prewhitening technique, sonar detection, split beam, weak target detection.

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Acoustic Source Localization Based on Generalized Cross-correlation Time-delay Estimation

Cited by 57 publications

References 2 publications

A Sound Source Localization Device Based on Rectangular Pyramid Structure for Mobile Robot

A Sound Source Localization Device Based on Rectangular Pyramid Structure for Mobile Robot

A design of algorithm based on microphone array

Insight Into Split Beam Cross-Correlator Detector With the Prewhitening Technique

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