• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.5-172
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• 2001

Target Motion Analysis(TMA) for Passive Sonar Systems with bearing-only measurements needs to enhance system observability to improve target tracking performance by ownship maneuvering. However, tracking problem incurred by weak observaility result in slow convergence of the target estimates. On the other hand, active sonar systems do not have problem associated with system observaility. However, it drawback related to system survivability. In this paper, the algorithm that could be used in Active/passive Mixed-Mode Sonar Systems is proposed to analyze maneuvering target motion and to improve TMA performance. The proposed TMA algorithm is tested by a series of computer simulation runs and the results ...

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.5
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• pp.532-537
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• 2015

In this paper, we propose target range estimation method using ghost target in the submarine linear array sonar. Usually, when submarine detect target, they use passive sonar detection to avoid self-disclosure by active sonar transmission. But, originally, passive linear array sonar have limitation for target range estimation and additional processing is required to get target range information. For the case of near-field target, typical range estimation method is using multiple information by multipath effect in underwater environment. Acoustic signal generated from target are propagated along with numerous multipath in underwater environment. Since multipath target signals received in the linear array sonar have different conic angles each other, ghost target is appeared at the bearing different with real target bearing and sonar operator can find these information on the operation console. Under several assumption, this geometric properties can be analysed mathematically and we get the target range by derivation of this geometric equations using measured conic angles of real target and ghost target.

• 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 Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• 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 the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.33-40
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• 2006

In towed array passive sonar system, sonar operators cannot detect and track the all targets simultaneously in the omni-directional area by just Operator Initiated Tracking(OIT). In this paper, omni-directional automatic target detection and tracking algorithm is described and optimize the parameters through ocean data to overcome the drawbacks of OITs. The algorithm is verified through sea trials with submarines.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.76-84
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• 2000

As first step of any acoustic defence system, a attacking target warning system needs to be extremely reliable. This means the system must ensure a high probability of target classification together with a very low false alarm rate. In this paper, a algorithms for underwater target automatic classification is available for use in the passive sonar will be presented. In first, we will describe the precise automatic extraction of frequency lines for the detection of acoustic signatures. Also, a neural network and fuzzy based algorithms for target classification will be described. Thus the performances of these algorithms are very good with a high probability of classification.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.549-558
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• 2020

In this paper, the method is discussed such that the robustness of automatic initiated narrowband target tracking is improved in passive sonar. In the case of automatic tracking initiation as target in passive sonar, due to a number of clutter, the clutter is initiated as target and tracked which prohibits the operation capability. The associated probability and information entropy of measurements, extracted from detection data, is calculated to keep going on automatic target initiation and tracking of true target, but reduce the automatic initiation and tracking of clutter. If the association probability and information entropy of the extracted measurements is satisfied for the predefined conditions, the procedure of automatic initiation begins. Using sea-trial data, simulations are executed and the results from the proposed method indicate that it keeps the automatic target initiation and tracking of true target and suppresses the automatic target initiation and tracking of clutters in contrary to the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.629-634
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• 2009

In real-time system application, the feature extraction and scoring algorithm for classification of the passive sonar target has the following problems: it requires an accurate and efficient feature extraction method because it is very difficult to distinguish the features of the propeller shaft rate (PSR) and the blade rate (BR) from the frequency spectrum in real-time, it requires a robust and effective feature scoring method because the classification database (DB) composed of extracted features is noised and incomplete, and further, it requires an easy design procedure in terms of structures and parameters. To solve these problems, an intelligent feature extraction and scoring algorithm using the evolution strategy (ES) and the fuzzy theory is proposed here. To verify the performance of the proposed algorithm, a passive sonar target classification is performed in real-time. Simulation results show that the proposed algorithm effectively solves sonar classification problems in real-time.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.145-151
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• 2024

Recently, ship hull-mounted passive sonar system solution is needed in the perspective of improving target detection and elimination of vibration-induced noise. Our research team suggests acousticvibration matching method using front and rear signal of a sensor as the improvement of the problem above. Thus in this paper, theoretical background about matching method and its application on finite element method based multi-physics simulation are described. Furthermore, it is shown that target detection and hull vibration performance are improved by using matching method under the condition of our sensor system. Finally, practicality and future research are discussed.