• The Journal of the Acoustical Society of Korea
• /
• v.13 no.2
• /
• pp.30-37
• /
• 1994

Since the morden targets are of high speed and getting quiet in both active and passive mode, the necessities of developing advanced SONAR system capable of performing target motion analysis (TMA) and target classification are evident. In order to develop such a system, the scattering mechanism of complex bodies needs to be, some extent, fully understood and modeled. In this paper, MOving Spread Target(MOST) signal simulation model is presented and discussed. The model is based on the highlight distribution method, and simulates pulse elongation of spread target, doppler effect due to kinematics of the target as well as SONAR platform, and distribution target strength of each highlight point (HL) with directivity. The model can be used in developing and evaluating advanced SONAR system through system simulation, and can also be used in the development of target state estimation algorithm.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.51 no.3
• /
• pp.321-327
• /
• 2018

To classify seafloor sediments using a probabilistic neural network (PNN), the frequency-dependent characteristics of broadband acoustic scattering, which make it possible to qualitatively categorize seabed type, were collected from three different geographical areas in Korea. The echo data samples from three types of seafloor sediment were measured using a chirp sonar system operating over a frequency range of 20-220 kHz. The spectrum amplitudes for frequency responses of 35-75 kHz were fed into the PNN as input feature parameters. The PNN algorithm could successfully identify three seabed types: mud, mud/shell and concrete sediments. The percentage probabilities of the three seabed types being correctly classified were 86% for mud, 66% for mud/shell and 72% for concrete sediment.

• Journal of Sensor Science and Technology
• /
• v.32 no.5
• /
• pp.313-319
• /
• 2023

In this study, we propose a method to improve the accuracy of acoustic odometry using optimal frame interval selection for Fourier-based image registration. The accuracy of acoustic odometry is related to the phase correlation result of image pairs obtained from the forward-looking sonar (FLS). Phase correlation failure is caused by spurious peaks and high-similarity image pairs that can be prevented by optimal frame interval selection. We proposed a method of selecting the optimal frame interval by analyzing the factors affecting phase correlation. Acoustic odometry error was reduced by selecting the optimal frame interval. The proposed method was verified using field data.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.6
• /
• pp.9-16
• /
• 1999

As a part of target motion analysis(TMA) with highly noisy bearings-only measurements from a passive sonar system, a nonlinear batch estimator is proposed to provide the initial estimates to a sequential estimator called the modified gain extended Kalman filter(MGEKF). Based on the system observability analysis of passive target tracking, a practical and effective method is suggested to determine the observer maneuvers for improved TMA performance through system observability enhancing. Also suggested is a method to determine observer location for enhanced system observability at the initial phase of TMA from various engagement boundaries which represent the relationship between observer-target relative geometrical data and system observability. The proposed TMA methods are tested by a series of computer simulation runs.

• Journal of the Korean Society of Systems Engineering
• /
• v.15 no.1
• /
• pp.16-24
• /
• 2019

In this study, an improved method of setting the RAM goals for surveillance system using OMS/MP and field operations data of similar systems is suggested and a case study of surveillance system A is given. Newly suggested methods for setting the RAM goals consist of the procedures such as On/Off time analysis of configuration equipment based on OMS/MP, field operations data analysis of similar systems, adjustment of preventive maintenance time, the number of corrective maintenances, and TALDT in wartime, introducing new subsystem to reliability structure of surveillance system, and reflecting expert's opinion. A case study of surveillance system A shows that newly suggested method in this study for setting the RAM goals is reasonably acceptable and practically applicable to other similar systems.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.6
• /
• pp.428-436
• /
• 2004

Synthetic Aperture Sonar is a technique of extending Physically limited length of an array by signal processing to enhance bearing resolution of a system. The previous techniques estimate most or away shapes as linear. so when towed array shapes are distorted. this can create a deviation from actual situation. In this paper. we estimated perturbed away shapes. and compensated distortion by using estimated array shapes and synthesized arrays in aperture domain. As experimental data, we used the one obtained from towed array in neighboring waters of the Korean peninsula. We extended array by compensating differences in time and spatial position between overlapped subarrays by using SAS techniques. In simulation results. we confirmed that the bearing resolution was enhanced.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.5
• /
• pp.601-614
• /
• 2012

Since the optimized use of sonar systems available for detection is a very practical problem for a given ocean environment, the measure of mission achievability is needed for operating the sonar system efficiently. In this paper, a theory on Measure Of Effectiveness(MOE) for specific mission such as detection is described as the measure of mission achievability, and a recursive Cumulative Detection Probability(CDP) algorithm is found to be most efficient from comparing three CDP algorithms for discrete glimpses search to reduce computation time and memory for complicated scenarios. The three CDPs which are MOE for sonar-maneuver pattern are calculated as time evolves for comparison, based on three different formula depending on the assumptions as follows; dependent or independent glimpses, unimodal or non-unimodal distribution of Probability of Detection(PD) as a function of observation time interval for detection. The proposed CDP algorithm which is made from unimodal formula is verified and applied to OASPP(Optimal Acoustic Search Path Planning) with complicated scenarios.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.2
• /
• pp.44-51
• /
• 2001

This Paper the practical echo signal synthesis model to predict the target strength and signal shape of a submarine for a valuable tool to active sonar engineer. It is based on UTAHID (Underwater TArget by Highlight Distribution) model which is relocated highlight points along to external hull for aspect angle, and synthesized echo signal by modified grouping highlights to internal scatter cloud. Proposed model is analyzed target strength characteristics on various incident pulse length, and synthesis signal signature, target time spreading loss, echo elongation effect and so on. Thus it can be efficiently used in various real systems related to underwater target echo signal synthesis, that is, active sonar, acoustic countermeasure and surveillance system.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.1
• /
• pp.96-105
• /
• 2019

Ocean reverberation is the most limiting factor in designing realistic and real-time system for sonar simulator. The simulation for an ocean reverberation requires a lot of computational loads, so it is hard to embed program and generate real-time signal in the sonar simulator. In this study, we simulate a time-domain bottom reverberation signal based on Harrison's energy-flux bottom reverberation model by applying Doppler effects as ship maneuvering and autoregressive model. Finally, the bottom reverberation signal with realistic characteristics could be generated for the simulation of ONR reverberation modeling workshop-I problem XI and East Sea ocean environments.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.234-242
• /
• 2024

We propose a passive sonar signal classification algorithm using Graph Neural Network (GNN). The proposed algorithm segments spectrograms into image patches and represents graphs through connections between adjacent image patches. Subsequently, Graph Convolutional Network (GCN) is trained using the represented graphs to classify signals. In experiments with publicly available underwater acoustic data, the proposed algorithm represents the line frequency features of spectrograms in graph form, achieving an impressive classification accuracy of 92.50 %. This result demonstrates a 8.15 % higher classification accuracy compared to conventional Convolutional Neural Network (CNN).