• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.2
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• pp.93-101
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• 2022

It is essential to prevent LoC(Loss-of-Control) or upset situations caused by stall, icing or sensor malfunction in aircraft, because it may lead to the crash of the aircraft. With this regard, it is crucial to correctly identify the dynamic characteristics of aircraft in such upset conditions. In this paper, we present a SID(System IDentification) method utilizing the moving-window based least-square and the adaptive-order ZKF(Zonotopic Kalman Filter), which is more effective than the existing Kalman-filter based SID for the aircraft in upset condition at a high angle of attack with temporary sensor malfunction. The proposed method is then tested on real flight data and compared with the existing one.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.10-17
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• 2019

In High Dynamic Range (HDR) image processing, tone mapping is the process to compress an input image into a Low Dynamic Range (LDR) image. In most cases, the reason that detail preservation is prior to take over tone mapping is that the dynamic range is significantly different between input and output images. In the case of iCAM06, details are separated by using a bilateral filter, however, it causes noise amplification at the dim surround region. Thus, we suggest that the detail signal, which is separated from the bilateral filter, is combined with the base signal after an adaptive Kalman filter is applied according to the local standard deviation. We confirmed that the proposed method enhances the HDR images quality by checking the noise reduction in a dim surround region.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.219-228
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• 2007

In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1837-1845
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• 2015

The longitudinal velocity is necessary for accurate vehicular positioning in urban environment. The pitch angle, which is a road slope, should be calculated to acquire the longitudinal velocity. However, it is impossible to consider very accurate pitch, when using a sensor and an algorithm. That's why process noise and positioning stimation error of IMU should be adjusted to the driving environment and fuse GPS, OBD data with ACF which consist of AKF, CF in this paper. Then, final pitch angle which is appropriate for driving environment is estimated by IMMKF in order to optimize the system model according to road slope models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.501-507
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• 1999

At the mobile unit for adaptation the propagation environment, it is necessity to adapt very fast the weight coefficient vector of adaptive array antenna In this paper, for the BPSK and BFSK signals with S/I=2, S/N=10 subband adaptive array signal processing method to the linear array antenna using the LMS & the Kalman filter algorithm is proposed. For the 4 elements equidistance linear array antenna systems LMS and Kalman algorithms with subband adaptive instruction principles using the subband signal processing method are adopted and the computer simulation results to the constant amplitude envelope signals such as BPSK or BFSK can be seen that the convergence characteristics of directional patterns and the signal following characteristics are more fast and stable.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.506-509
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• 2005

An adaptive ${\alpha}-{\beta}$ tracker is proposed for tracking maneuvering targets with a track-while-scan radar system. The tracker gain is updated on-line corresponding to the adjusted process noise variance which is obtained via time averaging of the process over a sliding window. The adjusted process noise variance is used to compute the maneuverability index for the tracker gain based on the steady-state Kalman filter equation for each epoch. It is shown via simulation that the proposed approach provides robust and accurate position estimates during the target maneuver while the performance of the conventional ${\alpha}-{\beta}$ tracker is shown much degraded.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.24-36
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• 2011

A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.57-65
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• 2012

To neutralize fast Anti-Tank Guided Missiles(ATGMs) or Anti-Tank Rockets(ATRs) projected at short ranges, the trajectories and times that the threats arrive at hard-kill systems should be predicted precisely. The trajectories of ATGMs or ATRs are almost stationary but the velocity and acceleration are very changeable in the terminal stage, so that it is needed to predict the characteristics of ATGMs and ATRs for filtering. In this paper the Fuzzy Rule based Adaptive Kalman Filter(FRAKF) is proposed to estimate the position, velocity and acceleration of the threats with accuracy and the performance of it is compared with the existing tracking filter considering the maneuvering characteristics of threats.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.118-121
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• 2002

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seliously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.