• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.100-105
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• 2014

This paper comparatively analyze to integration case to have a influence detection range estimation about radar cross section in radar system. This paper estimate detection range used to probability of detection in radar equation that used to swerling case 1 in case of radar cross section is small and used to swerling case 3 in case of radar cross section is large. Through simulation, coherent integration and non-coherent integration about swerling case difference were comparatively analyzed. Through simulation, non-coherent integration case is outstanding detection range and we known that coherent integration don't suitable for detection range estimation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.113-117
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• 2014

This paper comparatively analyze to integration case to have a influence detection range estimation about radar cross section in radar system. This paper estimate detection range used to probability of detection in radar equation that used to swerling case 1 in case of radar cross section is small and used to swerling case 3 in case of radar cross section is large. Through simulation, coherent integration and non-coherent integration about swerling case difference were comparatively analyzed. In the result of comparative analysis, non-coherent integration case is outstanding detection range and we known that coherent integration don't suitable for detection range estimation.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.92-97
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• 2014

A novel method for extracting frequency slippage signal from radar full pulse sequence is presented. For the radar full pulse sequence received by radar interception receiver, radio frequency (RF) and time of arrival (TOA) of all pulses constitute a two-dimensional information sequence. In a complex and intensive electromagnetic environment, the TOA of pulses is distributed unevenly, randomly, and in a nonstationary manner, preventing existing methods from directly analyzing such time series and effectively extracting certain signal features. This work applies Gaussian noise insertion and structure function to the TOA-RF information sequence respectively such that the equalization of time intervals and correlation processing are accomplished. The components with different frequencies in structure function series are separated using empirical mode decomposition. Additionally, a chaos detection model based on the Duffing equation is introduced to determine the useful component and extract the changing features of RF. Experimental results indicate that the proposed methodology can successfully extract the slippage signal effectively in the case that multiple radar pulse sequences overlap.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.311-314
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.813-826
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• 2018

Recently, weather radar system has been widely used for effectively monitoring near real-time weather conditions. The radar rainfall estimates are generally relies on the Z-R equation that is an indirect approximation of the empirical relationship. In this regards, the bias in the radar rainfall estimates can be affected by spatial-temporal variations in the radar profile. This study evaluates the uncertainty of the Z-R relationship while considering the rainfall types in the process of estimating the parameters of the Z-R equation in the context of stochastic approach. The radar rainfall estimates based on the Bayesian inference technique appears to be effective in terms of reduction in bias for a given season. The derived Z-R equation using Bayesian model enables us to better represent the hydrological process in the rainfall-runoff model and provide a more reliable forecast.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.303-306
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.6
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• pp.433-440
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• 2018

A radar receives reflected signals from various objects to detect a target. Undesired object, called clutter, as well as the target generates reflected signals. The clutter radar cross section(RCS) is dependent on many factors, which are the antenna pattern, distance between the radar and the target, and the height of the target and the radar. Herein, surface clutter RCS for ground-based radar is analyzed, and the effect of the surface clutter RCS on the received signal is investigated.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.11
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• pp.1225-1231
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• 2003

In this paper, we present the analysis of electromagnetic scattering from arbitrarily shaped three-dimensional conducting objects coated with dielectric materials. The integral equation treated here is the combined field integral equation(CFIE). The objectives of this paper is to illustrate that only the CFIE formulation is a valid methodology in removing the interior resonance problem, which occurs at a frequency corresponding to an internal resonance of the structure. Numerical results of radar cross section for coated conducting structures are presented and compared with other available solutions.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1373-1389
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• 2019

KOMPSAT-5 is the first satellite in Korea equipped with X-band Synthetic Aperture Radar (SAR) instrument and has been operated since August 2013. KOMPSAT-5 is used to monitor the global environment according to its observation purpose and the availability of KOMPSAT-5 is also highlighted as the need of high resolution wind data for investigating the coastal region. However, the previous study for the validation of wind derived from KOMPSAT-5 showed that the accuracy is lower than that of other SAR satellites. Therefore, in this study, we developed the correction equation of normalized radar cross section (NRCS or backscattering coefficient) for improvement of wind from the KOMPSAT-5 and validated the effect of the equation using the in-situ measurement of ocean buoys. Theoretical estimated NRCS and observed NRCS from KOMPSAT-5 showed linear relationship with incidence angle. Before applying the correction equation, the accuracy of the estimated wind speed showed the relatively high root-mean-square errors (RMSE) of 2.89 m s^-1 and bias of -0.55 m s^-1. Such high errors were significantly reduced to the RMSE of 1.60 m s^-1 and bias of -0.38 m s^-1 after applying the correction equation. The improvement effect of the correction equation showed dependency relying on the range of incidence angle.

• Journal of the Korean Institute of Navigation
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• v.1 no.1
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• pp.17-26
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• 1977

A large number of the set-nets are set in Namhaedo coast of Korea. The floats of these set-nets are not only small even in case of large floats but also they scarcely have distinguishable marks such as light buoys or flags, so that they are very hard to be recognized by naked eyes and thus became probable obstacles to navigation for the passing ships and the fishing vessels. In order to research the capability of detecting such nets with Radar, the author investigated a maximum detectable range of the ordinarly large floatsand of a floating corner reflectors of various size and shape by Radar. The results obtained are as follows; 1. A maximum detectable range of large floats at a close range can be calculated by the Radar equation in sufficient accuracy. 2. Large floats of the large set-nets are also detectable by Radar even though it's detectable range boundary was within 0.2-0.65 miles. And the Radar picture of large floats was easier to be found with somewhat higher setting of the gain control on shorter range scale of the 1 mile. 3. Floating corner reflector rather suitable for set-net floats of "S" type reflector proposed in this paper, of which the dimension must be above 17cm in diameter to be detectable by Radar at 2 miles.t 2 miles.