• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.649-653
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• 2006

Engine Noise is composed of the mechanical and combustion noise. The contribution of combustion noise is generally bigger than the contribution of the mechanical noise at idle condition in DI diesel engine. That noise usually makes a roughness problem at the fundamental engine order. It is difficult to remove the modulation frequency so we have to directly reduce the combustion noise. The key effect of combustion noise reducing solution is the modification of the combustion pressure profile. It is accomplished by the multiple injection method and we solved the 400Hz combustion noise and improved the sound quality at idle condition in DI diesel engine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.469-474
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• 2011

This paper presents the intelligent tracking method for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. K-means clustering and TS fuzzy system are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by K-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. While calculating expected value, the non-linearity of the maneuvering target is recognized as linear one by dividing acceleration and the capability of Kalman filter is kept in the filtering process. The error for the non-linearity is compensated by approximated acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.554-564
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• 2020

In environment of torpedo firing, underwater acoustic signal is generated by target and noise. Sound wave which is generated from acoustic signal is propagated by seawater and it is received through the sonar(sound navigation and ranging) system mounted on torpedo. In the ocean, acoustic signal or sound wave from target that is generated by the spread of broadband can be attenuated by ambient noise and can be lost by medium and environment. This research is designed to support teamwork training in Naval operations by constructing a simulation system that is more similar to the real-world conditions. This paper attempts to research the modeling of target detection and to develop the simulation of torpedo sonar(TOSO). In order to develop the realistic simulation, we researched the broadband sound modeling of target and noise source, the modeling of acoustic transmission loss by chemical component of seawater, and the modeling of signal attenuation by ambient noise environment which is approximated by experimental measurements in seawater surrounding the Korea Peninsular and by experience of Navy's actual torpedo firing. This research contributed to constructing more practical simulation of torpedo firing in real time and the results of this research were used to develop a teamwork training system for the Navy and their education.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.387-395
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• 2019

TMA (Target Motion Analysis) in passive sonar is generally conducted with the bearing only or the bearing frequency. In order to conduct TMA fast and accurately, it is essential to estimate a initial target maneuver precisely. The accuracy of TMA can be improved by using SNR (Signal to Noise Ratio) information and acoustic propagation model additionally. This method assumes that the radiated noise level of the target is known, but the accuracy of TMA can be degraded due to a mismatch between the assumed radiated noise level and the actual radiated noise level. In this paper, TMA with the acoustic propagation model, bearing measurements, and SNR information is conducted in the ocean environment of South Korea (East Sea/ Yellow Sea/ South Sea). And the performance analysis of TMA for the mismatch in the radiated noise is presented.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.26-29
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• 2001

In a target tracking problem the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In most nonlinear situations an Extended Robust Kalman Filter(ERKF) can yield acceptable performance as long as the noises are white Gaussian. However, an Extended Robust $H_{\infty}$ Filter (ERHF) can yield acceptable performance when the noises are Laplacian. In this paper, we use the Interacting Multiple Model(IMM) estimator for the problem of target tracking with glint noise. In the IMM method, two filters(ERKF and ERHF) are used in parallel to estimate the state. Computer simulations of a real target tracking shows that hybrid filter used the IMM algorithm has superior performance than a single type filter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.461-466
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• 2012

Customers want to have more convenient and comfortable vehicle. Motor-on-caliper EPB(Electrical Parking Brake) System is one of the new systems for customer's convenience. It is applied for Midsize vehicle for reducing weight/price compared to cable puller type EPB. In this paper we studied sound quality improvement of motor-on-caliper EPB system. We developed the sound quality index and suggested the interior sound quality target value. To meet the target value cascading target was also suggested. EPB motor vibration level & sound radiation level, vibro-acoustic transfer function level from EPB to interior was defined. To find out effective way of sound quality improvement and find cascading target, TPA(Transfer Path Analysis) was carried out.

• Journal of the Korean Society of Safety
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• v.15 no.3
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• pp.88-95
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• 2000

The level of noise produced by machinery and its arrangement insides a factory is indicated to be a maximum of 96.1 dB(A). The maximum level of noise from a commoner's house outside the factory is shown to be 62.9 dB(A), which exceeds 60 dB(A), the permitted limit of noise level in a time period of day. us study has predicted the level of noise reduction according to a step by step prevention plan by considering the characteristics of the causes of noise, the permitted limit of noise levels, problems and economical efficiency attendant upon the noise prevention measures. Establishing target levels of noise each of the three steps of the noise prevention plan. The predicted level of noise at the place of a commoner's house in accordance with the first step is 50.0 - 59.0 dB(A), and can satisfy the permitted limit of noise in a time period of the day. In taking prevention measures for the second step, the noise level is 50.7 - 53.6 dB(A) which is less than 55 dB(A) in a time period of the evening, the permitted limit of noise in a time period of night., and it can meet 47.4 - 50.3 dB(A) in the third step.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.255-263
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• 2012

This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.

• 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.