• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.580-586
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• 2019

In this paper, we propose a biomimetic communication method using a dolphin whistle to covertly transmit the communication signal. A conventional CSS (Chirp Spread Spectrum) modulation technique divides dolphin whistle into several slots and modulates with up and down chirp signals. That causes the time-frequency characteristic difference between the original dolphin whistle and the camouflage performance is degraded. In this paper, we propose a delay based modulation scheme to eliminate distortions. The simulation results show that the bit error rate of the proposed method is better performance than that of the conventional CSS modulation method by about 3.5 dB to 8 dB. And the camouflage performance that evaluated through the cross correlation in the time-frequency domain is also better than that of the CSS modulation method.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.370-381
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• 2021

This paper presented an efficient transceiver structure of multiband Frequency Shift Keying (FSK) signals with direct sequence spread spectrum for maintaining covertness and performance. In aspect to covertness, direct sequence spread spectrum method, which multiplying by Pseudo Noise (PN) codes whose rate is much higher than that of data sequence, is employed. In aspect to performance, in order to overcome performance degradation caused by multipath and Doppler spreading, we applied multiband, turbo equalization, and weighting algorithm are applied. Based on the simulation results, by applying 4 number of multiband and number of chips are 8 and 32, experiments were conducted in a lake with a distance of moving from 300 m to 500 m between the transceivers. we confirmed that the performance was improved as the number of bands and chips are increased. Furthermore, the performance of multiband was improved when the proposed weighting algorithm was applied.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.412-421
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• 2018

The Line array sonar consisting of several hydrophones increases array gain and improves the performance for detecting the direction of the target compared to single hydrophone. However, line array sonar produces the bearing error that makes it difficult to determine the bearing of incoming source signal due to the relation between bearing angle of target and vertical angle of multipath signals. Vertical angles of multipath are varied with the geometry of receiver and target and various underwater environments, therefore it is necessary to consider the bearing error to estimate accurately the bearing of the target. In this study, acoustic modelling was performed to understand the effect of multipath signals on the target signal. The errors of bearing angle estimated from the bottom bounced signals are calculated with several environment. In addition, the expected bearing line, as a function of source-receiver range, compensated for the bearing error is predicted from the estimated bearing angle.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.461-467
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• 2022

Sonobuoy is a disposable device that collects underwater acoustic information and is designed to transmit signals collected in a particular area to nearby aircraft or ships and sink to the seabed upon completion of its mission. In a conventional sonobouy signal transmission and reception system, collected signals are modulated and transmitted using techniques such as frequency division modulation or Gaussian frequency shift keying, and received and demodulated by an aircraft or a ship. However, this method has the disadvantage of the large amount of information to be transmitted and low security due to relatively simple modulation and demodulation methods. Therefore, in this paper, we propose a method that uses an autoencoder to encode a transmission signal into a low-dimensional latent vector to transmit the latent vector to an aircraft or ship and decode the received latent vector to improve signal security and to reduce the amount of transmission information by approximately a factor of a hundred compared to the conventional method. As a result of confirming the sample spectrogram reconstructed by the proposed method through simulation, it was confirmed that the original signal could be restored from a low-dimensional latent vector.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.2
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• pp.141-152
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• 2022

As a method to understand the ecological habits around the artificial reef, various reports such as fishing gear survey, diving, sound survey, underwater CCTV and camera, etc. are reported. Among them, the sound survey method is carried out by installing an acoustic system on the ship and can be investigated regardless of the marine environment such as time constraints and turbidity. Such method, however, takes a lot of manpower and time as the ship travels at a constant speed. Investigations around artificial reefs are being conducted in an artificial way, and a lot of time and labor are consumed as such. Maritime buoys have been operated for various purposes such as route signs, weather observation, marine environment monitoring and defense monitoring for navigation safety in the past, but studies on monitoring systems for ecological habits and distribution of fish using marine buoys are remarkably insufficient. Therefore, this study aims to develop a system that allows users to directly monitor fish group detector data by estimating the distribution of fish groups around artificial reefs and using wireless communication at sea. In order to confirm the suitability of the maritime buoy used in this study, it was operated to compare data using LTE-equipped buoys capable of wireless communication and a data logger-type system buoy. Data transmission of buoys capable of LTE communication was carried out in a 10-minute ON, 10-minute OFF method due to the limitation of the power supply capacity, and data of the data logger-type buoy received full data. We compared and analyzed the data received from the two fish detectors. It is expected that real-time monitoring of the wireless buoy detection device using LTE will be possible through future research.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.262-269
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• 2023

In this paper, we propose a Linear Prediction (LP) analysis-based feature for detecting Snapping Shrimp (SS) Noise (SSN) in underwater acoustic data. SS is a species that creates high amplitude signals in shallow, warm waters, and its frequent and loud sound is a major source of noise. The proposed feature takes advantage of the characteristic of SSN, which is sudden and rapidly disappearing, by using LP analysis to detect the exact noise interval and reduce the effects of SSN. The error between the predicted and measured value is large and results in effective SSN detection. To further improve performance, a constant false alarm rate detector is incorporated into the proposed feature. Our evaluation shows that the proposed methods outperform the state-of-the-art MultiLayer-Wavelet Packet Decomposition (ML-WPD) in terms of receiver operating characteristic curve and Area Under the Curve (AUC), with the LP analysis-based feature achieving a higher AUC by 0.12 on average and lower computational complexity.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.199-209
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• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.345-356
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• 2023

Target signal of passive sonar shows narrow band harmonic characteristic with a variation in intensity within a few seconds and long term frequency variation due to the Lloyd's mirror effect. We propose a signal classification algorithm based on Gated Recurrent Unit (GRU) that learns local and global time series features. The algorithm proposed implements a multi layer network using GRU and extracts local and global time series features via dilated connections. We learns attention mechanism to weight time series features and classify passive sonar signals. In experiments using public underwater acoustic data, the proposed network showed superior classification accuracy of 96.50 %. This result is 4.17 % higher classification accuracy compared to existing skip connected GRU network.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.500-510
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• 2023

Passive sonar signals mainly contain both normal and abnormal signals. The abnormal signals mixed with normal signals are primarily detected using an AutoEncoder (AE) that learns only normal signals. However, existing AEs may perform inaccurate detection by reconstructing distorted normal signals from mixed signal. To address these limitations, we propose an abnormal signal detection model based on a Recurrent Neural Network (RNN) and vector quantization. The proposed model generates a codebook representing the learned latent vectors and detects abnormal signals more accurately through the proposed search process of code vectors. In experiments using publicly available underwater acoustic data, the AE and Variational AutoEncoder (VAE) using the proposed method showed at least a 2.4 % improvement in the detection performance and at least a 9.2 % improvement in the extraction performance for abnormal signals than the existing models.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.138-144
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• 2024

This paper presents a bistatic to monostatic conversion technique to analyze the bistatic target strength of submarines. The technique involves determining the transmission path length of acoustic waves, which are emitted from a source, scattered off an underwater target, and eventually received by a receiver. By generating a corresponding virtual scattering surface, this method effectively transforms the target strength analysis problem from bistatic to monostatic. The converted monostatic target strength problem can be assessed using a well-established monostatic numerical methods. The bistatic target strength analysis for Benchmark Target Strength Simulation (BeTTSi), a widely used target strength model were performed. The results were compared with those calculated by boundary element methods and Kirchhoff approximation, and confirmed the validity and the practical applicability of the proposed analysis technique for evaluating submarine target strength.