Biologically inspired underwater acoustic communication based on discrete cosine transform

Ma, Tianlong; Qiao, Gang; Liu, Songzuo; Mazhar, Suleman; Zheng, Naihua; Pan, Chenyu

doi:10.1016/j.apacoust.2022.108930

Cited by 4 publications

(1 citation statement)

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“…These facts explain that there are many techniques develop to reduce noise such as deep learning approach [1], value decomposition algorithm [2], wavelet transform [3], or neural networks [4]. These techniques are chosen to cope challenges in applying underwater acoustics signal for communications such as frequency-dependent attenuation [5], short range of communication [6], and very low bandwidth [7]. In the application of underwater communication, the ideal signal is an acoustic signal.…”

Section: Introductionmentioning

confidence: 99%

Underwater Acoustic Intensity Analysis using Noise Assisted-MEMD with Varying Distances

Fajarwati,

Feriadi,

Widjiati

2023

Jurnal Teknik Elektro

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With current developments, underwater communication using acoustic signals is widely used. Many things need to be prepared to support a reliable underwater communication system, such as taking measurements in a test tank to find out the correct measurement configuration. Underwater acoustic intensity measurements, which are detailed in this paper, are performed in the test tank using distance variation schemes. Measurements were made at various distances of 4, 10, 20, and 50 meters from the signal source. The hydrophone that was used has a sensitivity of -180 dB re 1V/µPa. The hydrophone was placed at a depth of 2 meters below the surface of the water in the test tank, which divided the test tank depth in half to ensure that reflections from the bottom and the surface were kept to a minimum. However, the problem is that there are noisy signals at different frequencies. This paper proposes a method using Noise Assisted - Multivariate Empirical Mode Decomposition (NA-MEMD) to decompose the signal and then calculate the sound intensity. The result shows that an increase in the distance between the transmitter and receiver, also causes a change in the intensity with an average change of 0.467 dB/meter. It is concluded that the NA-MEMD approach was shown to be successful in decomposing the intended signal from the noise to equalize the quality of the signal received at different distances, and the correlation between intensity value and change in distance is resilient, with a correlation value of 0.98, indicating a very strong correlation.

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