• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.395-402
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• 2006

When an active SONAR works in the subsurface. its detection Performance is limited by the reverberation. The winds Play a primary role in the Production of bubbles in the ocean. And the bubbles as efficient scatters contribute to the reverberant field. In this Paper the effects of wind-generated bubbles on sound propagation in the subsurface are investigated as a mid-frequency Hull-mounted SONAR works. The active signal excess is calculated at source depths 3. 5. and 10m considering bubble layer for frequencies 5. 7.5, and 10kHz. The change of the near-surface sound speed tend to increase surface reverberation levels and change the active signal excess. In the 10m/s winds. the maximum detection range reduces over 3km through the near-surface . The reason is the upper refraction due to the wind-generated bubbles.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.5
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• pp.538-547
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• 2015

The goal of this study is to develop an algorithm to propose optimal deployment of detection sensor nodes in the target area, based on a performance surface, which represents detection performance of active and passive acoustic sonar systems. The performance surface of the active detection system is calculated from the azimuthal average of maximum detection ranges, which is estimated with a transmission loss and a reverberation level predicted using ray-based theories. The performance surface of the passive system is calculated using the transmission loss model based on a parabolic equation. The optimization of deployment configurations is then performed by a hybrid method of a virtual force algorithm and a particle swarm optimization. Finally, the effectiveness of deployment configurations is analyzed and discussed with the simulation results obtained using the algorithm proposed in this paper.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.2
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• pp.35-40
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• 1997

The hysteresis control method has been frequently used for current control of power conversion equipments or motor drive systems. This method makes the measured signal follow the reference signal by changing the control signal whenever the error signal exceeds the preset band width. In this paper, hysteresis control method with fast response characteristics is applied for active noise control to suppress acoustic noise. Both Pentium processor and sound blaster 16 are used for experimental implementation, which executes A/D, D/A conversion and also is used as operating source of loudspeaker for audible noise cancellation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.418-424
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• 2018

Detection and classification of underwater targets is an important issue for both military and non-military purposes. Recently, many performance improvements are being reported in the field of pattern recognition with the development of deep learning technology. Among the results, DBN showed good performance when used for pre-training of DNN. In this paper, DBN was used for the classification of underwater targets using active sonar, and the results are compared with that of the conventional BPNN. We synthesized active sonar target signals using 3-dimensional highlight model. Then, features were extracted based on FrFT. In the single aspect based experiment, the classification result using DBN was improved about 3.83% compared with the BPNN. In the case of multi-aspect based experiment, a performance of 95% or more is obtained when the number of observation sequence exceeds three.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.87-94
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• 2007

In active sonar system, aspect angle and length of a target can be estimated by calculating the cross-correlation between left and right split-beams of a LFM(Linear Frequency Modulated) signal. However, high-resolution performances in bearing and range are required to estimate the information of a remote target. Because a certain higher sampling frequency than the Nyquist sampling frequency is required in this performance, an over-sampling process through interpolation method should be required. However, real-time implementation of split-beam processing with over-sampled split-beam outputs on a COTS(commercial off-the-shelf) DSP platform limits its performance because of given throughput and memory capacity. This paper proposes a cumulative processing algorithm for split-beam processing to solve the problems. The performance of the proposed method was verified through some simulation tests. Also, the proposed method was implemented as a real-time system using an ADSP-TS101.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.77-84
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• 1998

The continuous time signal system by development of CMOS technology have been receiving consideration attention. In this paper, Low pass filter using CMOS floating resistor have been designed with cut off frequency for speech signal processing. Especially a new floating resistor consisting entirely of CMOS devices in saturation has been developed. Linearity within $\pm$0.04% is achieved through nonlineartiy via current mirrors over an applied range of $\pm$1V. The frequency response exceeds 10MHz, and the resistors are expected to be useful in implementing integrated circuit active RC filters. The low pass filter designed using this method has simpler structure than switched capacitor filter. So reduce the chip area. The characteristics of the designed low pass filter using this method are simulated by pspice program.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.341-346
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• 2008

This paper is to develop a monitoring system with diagnosis for smart cargo sensors that is for management and maintenance of the liquid cargo ships. The main goal of the system is to achieve the total automation system of the cargo sensor. By this study, the active smart sensor for the liquid cargo ships is designed and developed that guarantees high-confidence, stability, and durability. The proposed system consists of a monitoring part of the steam pressure, high-level monitoring, over flowing monitoring, gas monitoring, and tank temperature monitoring. The signals transferred from each unit system are used for sensor diagnosis based on confidence and accuracy. Finally, in this study, the total supervisory monitoring system is developed to maintain and manage the cargo effectively based on fault diagnosis and prognosis of the each sensor system.