• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.242-253
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• 2022

When the source waveform is unknown, the Green's function can be estimated by Ray-based Blind Deconvolution (RBD) based on the simple array signal processing. In previous papers, RBD was successfully demonstrated using simulation and experiments in shallow water environment. In this paper, we investigate the applicability of RBD for a long-range communication (e.g., 30 km, 60 km, and 90 km) in a deep water environment (1,000 m ~), using experimental data conducted in the east of Pohang, South Korea, in October 2018. Data results are presented to demonstrate Green's function estimation of a communication signal (2.2 kHz ~ 2.9 kHz) using a 16-element, 42-m long vertical array. The results show that the Green's function estimated from RBD is comparable to that of matched filter result. Additional communication performance at a maximum range of 90 km will be also presented.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.375-382
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• 2016

This paper presents the results for the performance improvement of underwater communication in a passive time reversal mirror (PTRM) using ray-based blind deconvolution (RBD). In conventional PTRM, the signal to be recovered is found from matched-filtering the received probe signal. However, the communication performance is degraded because the time-varying impulse response for each data frame is not reflected in the received probe signal. In this study, the time-variant transfer function is estimated from each received data frame using RBD, and the estimated time-variant transfer function is then used to recover the data signal using PTRM. The results from the experimental data show that the suggested method improves the communication performance when comparing with the conventional PTRM.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.331-339
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• 2016

This paper suggests an estimation method of the source signal and the channel impulse response (CIR) using ray-based blind deconvolution (RBD) in the underwater acoustic channel environment where Doppler effect exists by the relative motion between source and receiver. It is difficult to estimate the CIR on Doppler effect by the matched filter with a highly Doppler-sensitive waveform such as the m-sequence signal because Doppler shift can severely degrade the correlation between the received signal corrupted by Doppler effect and the original source signal. In this study, the Doppler-shifted source-signal's phase is estimated using the RBD, and the received signal is compensated by it to obtain the Doppler-corrected CIR. It is verified that using the matched filter with the received signal from the experimental data fails to estimate the CIR while the obtained CIR by the suggested method has the similarity to the propagation path of the ray model. Also, the results show that the reconstructed source signal using the RBD has the better Doppler shift compensation than the Doppler-shifted source signal derived from scattering function.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.378-386
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• 2017

Accurate distance measurement between maneuver target in underwater and measuring devices is required to perform quantitative test evaluation in marine weapons system R&D process. In general, the target distance is measured using a one-way ToA (Time of Arrival) method that calculates the time difference between transmitted and received signals from the two accurately synchronized devices. However, the distance estimation performance is degraded because of the multi-path environments. In this paper, the time-variant transfer function of complex underwater environment is estimated from each received data frame using RBD (Ray-based Blind Deconvolution), and the estimated time-variant transfer function is then used to get rid of the effect about complex underwater environment and to recover the data signal using PTRM (Passive Time Reversal Mirror). The result from the simulation and experimental data show that the suggested method improve the distance estimation performance when comparing with the conventional ToA method.