• Journal of the Society of Naval Architects of Korea
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• v.42 no.4 s.142
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• pp.299-306
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• 2005

To determine a guidance law which is suitable for Target Tracking System(TTS) of an underwater vehicle, the performance (hitting probability) of TTS were calculated with four different guidance schemes, considering underwater vehicle's manoeuvrability and characteristics of seeking equipment such as sonar To evaluate the performance of TTS with each guidance law, numerous target-tracking simulations of underwater vehicle were performed under the condition of target's various motion scenario. Furthermore, the effect of sonar characteristics to the performance of guidance law in TTS was studied by changing parameters of sonar such as frequency of ping and detecting error of target. The pursuit-tail guidance law showed the best performance among four different guidance laws. Complex motion of target from straight line to turning circle and zigzag movement, low frequency of sonar ping and large detecting error of target decreased the hitting probability.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.85-91
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• 2000

Underwater sensor accuracy test which measures the detection range and bearing accuracies of sonar simulates sonar transmitting ping and underwater radiating noise of target vessels. In this test, because the position of sonar target is the reference position of test, the sonar target position should be precisely estimated. Hence, this paper suggests to apply USBL algorithm which adopts cross phase spectrum of received sensor signals, and presents its performance by range and bearing estimation simulations. As a result of simulations, suggested algorithm shows good accuracy for underwater sensor accuracy test near 5㏈ SNR.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.456-464
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• 2013

Passive sonar in submarine can detect the target in long range and can attack using it. There are many noises which can be received at passive sonar of submarine. When noise received in the sonar it make diverse interference pattern depend on the ocean ambient and movement scenario. Interference pattern can be explained by theory of waveguide invariant. In this paper, analyze the interference pattern according to the relative motions of surface ship and submarine. And analyze the occurrence reason of 2 kinds of interference patterns those are usually display on the submarine console. The results show that if relative speed of submarine and target increase then gradient of interference pattern will increase. And closest point approach of submarine and target decrease then gradient of interference pattern will increase. Bathtube pattern usually appear when target pass though close to submarine and Pinetree pattern appear target pass though above of submarine.

• Journal of IKEEE
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• v.22 no.4
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• pp.1044-1049
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• 2018

CNN (Convolutional Neural Networks) is a neural network that models animal visual information processing. And it shows good performance in various fields. In this paper, we use CNN to classify target and non-target data by analyzing the spectrogram of active sonar signal. The data were divided into 8 classes according to the ratios containing the targets and used for learning CNN. The spectrogram of the signal is divided into frames and used as inputs. As a result, it was possible to classify the target and non-target using the characteristic that the classification results of the seven classes corresponding to the target signal sequentially appear only at the position of the target signal.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.163-169
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• 1997

The simulation of target-scattered echo with the moving sonar platform and target in 3-dimensional ocean environment is essential to validate and evaluate the performance of a sonar system. This paper presents the improved target signal simulation on the basis of the highlight(HL) model and its realtime algorithm. In order to simulate the scattering highlight, the highlight is represented as a directional scatterer. The realtime generation algorithm of the target signal is realized by use of DSP chip, TMS320C40, where the 40 channels are equally separated to form a parallel processing task in 4 processors. The presented realtime-version of target signal simulation can be used as a target signal simulator in the development of ACM(Acoustic Counter Measure) and advanced sonar signal processing techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.788-796
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• 2016

Bearing and frequency measurements of TMA (Target Motion Analysis) in passive line array SONAR have lower bearing rate and frequency doppler, and are not detected or tracked continuously because of various ocean environments. This is a main reason to effect the TMA performance and it takes a long time to get TMA solutions. We propose the bearing and frequency TMA(BFTMA) using accumulative batch estimation to solve the TMA problem of line array passive SONAR. The accumulative batch estimation structure is based on MLE (Maximum Likelihood Estimation) but used accumulative measurements. The accumulative batch estimation is applied for the BFTMA with nonlinear Kalman filter to estimate the target range, speed and course. Simulation and sea data analysis were carried out to verify the performance and applicability of the proposed techniques.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.586-593
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• 2012

The Navy is in the process of developing a sonar-operation strategy to increase the effectiveness of underwater target searching capability. HMS is the basic strategy to detect underwater targets. The advantages of HMS is that, it has a short preparation time to operate and can be always used regardless of sea conditions and weather. However, it is difficult to effectively detect underwater targets due to the interaction between marine environments and sonar-operations. During the research, the effectiveness of the HMS system's underwater target searching capability was analyzed by integrating various search and defense patterns, and environment conditions into the simulation. In the simulation the ship search an evasive target within a set region. The simulation presented results for an effective searching and defense methods of underwater targets. These research results can be used as foundation for advancing and improving the sonar operational tactics.

• Journal of Ocean Engineering and Technology
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• v.34 no.4
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• pp.277-284
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• 2020

Underwater acoustics, which is the study of phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. The main objective of underwater acoustic remote sensing is to obtain information on a target object indirectly by using acoustic data. Presently, various types of machine learning techniques are being widely used to extract information from acoustic data. The machine learning techniques typically used in underwater acoustics and their applications in passive SONAR systems were reviewed in the first two parts of this work (Yang et al., 2020a; Yang et al., 2020b). As a follow-up, this paper reviews machine learning applications in SONAR signal processing with a focus on active target detection and classification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.159-162
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• 2002

This paper deals with target positioning performance according to active sonar formation and measurement error. Generally, active sonar can be categorized into Monostatic, Bistatic and Multistatic cases and their error characteristics are different each other. In this paper, on the assumption that each receiver has two kinds of measurements； sum of distances, and a angle between receiver and target, we suggest least square(LS) method that combines the two measurements in Multistatic formation, and compare Multistatic case with Monostatic and Bistatic cases. Experimental results show that target positioning RMSE in Multistatic sonar is superior to those in Monostatic and Bistatic sonar by approximately 57％.