• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.12
• /
• pp.2346-2351
• /
• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.6
• /
• pp.1520-1529
• /
• 2013

In this paper, we propose and assess the performance of "H infinity filter ($H_{\infty}$, HIF)" and "cost reference particle filter (CRPF)" in the problem of tracking a target based on the measurements of the range and the bearing of the target. HIF and CRPF have the common advantageous feature that we do not need to know the noise statistics of the problem in their applications. The performance of the extended Kalman filter (EKF) is also compared with that of the proposed filters, but the noise information is perfectly known for the applications of the EKF. Simulation results show that CRPF outperforms HIF, and is more robust because the tracking of HIF diverges sometimes, particularly when the target track is highly nonlinear. Interestingly, when the tracking of HIF diverges, the tracking of the EKF also tends to deviate significantly from the true track for the same target track. Therefore, CRPF is very effective and appropriate approach to the problems of highly nonlinear model, especially when the noise statistics are unknown. Nonetheless, HIF also can be applied to the problem of timevarying state estimation as the EKF, particularly for the case when the noise statistcs are unknown. This paper provides a good example of how to apply CRPF and HIF to the estimation of dynamically varying and nonlinearly modeled states with unknown noise statistics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
• /
• pp.94-98
• /
• 2013

Transfer Path Analysis (TPA) is commonly used, by car makers and parts suppliers, analysis process to root the cause of NVH problems. In general, TPA is an analyzing technique to find the contributing factors of noise/vibration problems, and their transfer path in vehicle. However, not only TPA is used to analyze the source of NVH problems but also is used to predict NVH performance prior to the proto vehicle, or to set the development target for next new vehicle. Automotive parts manufacturing companies have to set NVH performance target when developing new systems just as car makers have NVH target set for new vehicle. Nevertheless, most of components are currently being developed based on subjective evaluation without an objective target. To judge the suitability of using TPA to set NVH target of electric parking brake, this research analyzed the transfer path by setting them in two points of view; Chassis Module and Electric Parking Brake, and comparing the measured value and calculated value. From this result, NVH target of electric parking brake will be approached in level of vehicle, system and component.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.05a
• /
• pp.283-286
• /
• 2002

In fiber optic sensor, the error of the measurement is influenced by the surface roughness of the target and surroundings, especially the outside light. To reduce or modify this error, the sensitivity of the fiber optic sensor and the noise change by the surface roughness of the target should be known. The purpose of this paper is to observe the sensitivity of the fiber optic sensor and the noise according to the surface roughness of the target.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.1
• /
• pp.62-68
• /
• 2014

Recently, MRI(magnetic resonance imager) scanner is continually used for medical diagnosis and many biomedical researches. When it operates, however, intense noise is generated. The SPL(sound pressure level) of the noise approaches 130 dB especially in 3 T(Tesla) MRI. Meanwhile, more than 3 T MRI scanners have been developed to get higher-resolution images, so louder noise is expected in the future. The intense noise makes patients feel nervous and uncomfortable. Moreover, it could possibly cause hearing loss to patient in extreme cases. For this reason, some active noise control systems have been researched. One of them used feedback Filtered-X LMS(FXLMS) algorithm which is able to control only narrowband noises and possible to diverge in severe case. In this paper, we determine the property of MRI noise. Using the property, we applied a method of open-loop and adaptive control for reducing MRI noise at target point inside bore. We verified performance of the method with computer simulation and preliminary experiment. The results demonstrate that the method can effectively reduce MRI noise at target point.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.8-13
• /
• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.25 no.8
• /
• pp.525-531
• /
• 2015

Driving sound is an effective element to promote the product identity of a vehicle by providing customers with attractive sound which reflects the concept of a vehicle. Recently, major automakers are focusing on the target sound setting so that the sound can represent the brand image as well as the unique concept of a vehicle. In this study, a new method of target setting for the driving sound will be introduced based on using formant filter and musical harmonics characteristics. In addition, a target sound suggested from this method will be realized and verified by using active noise control in vehicle.

• Proceedings of the KSR Conference
• /
• 1998.05a
• /
• pp.249-256
• /
• 1998

Design target values of transmission loss in a high-speed train wall are suggested by calculating the difference between interior and exterior noise levels of it. Exterior noise level distribution on the boundary of train wall is calculated by Sysnoise, with sound source input prepared by experiments. Two kinds of exterior sound sources are considered, the rolling noise of train wheels on the rail and the aerodynamic noise from the pantograph. Interior noise level is provided by high-speed design target. Transmission loss characteristics according to the frequency band are examined.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.9
• /
• pp.843-848
• /
• 2015

In this paper, The ARR-TSE (Automatic Range Restore - Triangulation based target Size Estimator) algorithm is presented for IIR (Imaging Infrared) seeker. The target size is important information for the IIR target tracking. The TSE (Triangulation based target Size Estimator) algorithm has suitable performance to estimate target size for static IIR target. but, the performance of the algorithm can be decreased by noise. In order to decrease influence of noise, we propose the ARR-TSE algorithm. The performance of proposed method is tested at target intercept scenario. The simulation results show that the proposed algorithm has the accurate target size estimating performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
• /
• pp.877-878
• /
• 2013