• Atmosphere
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• v.25 no.1
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• pp.19-30
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• 2015

The Ka-band cloud radar (KCR) has been operated by the National Institute of Meteorological Research (NIMR) of Korea Meteorological Administration (KMA) at Boseong National Center for Intensive Observation of severe weather since 2013. Evaluation of data quality is an essential process to further analyze cloud information. In this study, we estimate the measurement error and the sampling uncertainty to evaluate data quality. By using vertically pointing data, the statistical uncertainty is obtained by calculating the standard deviation of each radar parameter. The statistical uncertainties decrease as functions of sampling number. The statistical uncertainties of horizontal and vertical reflectivities are identical (0.28 dB). On the other hand, the statistical uncertainties of Doppler velocity (spectrum width) are 2.2 times (1.6 times) larger at the vertical channel. The reflectivity calibration of KCR is also performed using X-band vertically pointing radar (VertiX) and 2-dimensional video disdrometer (2DVD). Since the monitoring of calibration values is useful to evaluate radar condition, the variation of calibration is monitored for five rain events. The average of calibration bias is 10.77 dBZ and standard deviation is 3.69 dB. Finally, the statistical characteristics of cloud properties have been investigated during two months in autumn using calibrated reflectivity. The percentage of clouds is about 26% and 16% on September to October. However, further analyses are required to derive general characteristics of autumn cloud in Korea.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.217-222
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• 2015

Clustering is one of important data mining techniques known as exploratory data analysis and is being applied in various engineering and scientific fields such as pattern recognition, remote sensing, and so on. The method organizes data by abstracting underlying structure either as a grouping of individuals or as a hierarchy of groups. Weather radar observes atmospheric objects by utilizing reflected signals and stores observed data in corresponding coordinate. To analyze the radar data, it is needed to be separately organized precipitation and non-precipitation echo based on similarities. Thus, this paper studies to apply clustering method to radar data. In addition, in order to solve the problem when precipitation echo locates close to non-precipitation echo, fuzzy logic based clustering method which can consider both distance and other properties such as reflectivity and Doppler velocity is suggested in this paper. By using actual cases, the suggested clustering method derives better results than previous method in near-located precipitation and non-precipitation echo case.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1840-1846
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• 2011

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sensing purpose such as detection of moving targets and weather surveillance. The signal amplitude in the beat frequency band is the important parameter in the detection and tracking of targets. However, strong clutter echoes do exist in most radar operation environments and the system phase noise spreads both the clutter and signal echoes of the target. In this paper, the effects of this system phase noise are analyzed concerning the clutter and the signal beat spectrum. It is shown that the separation capability of adjacent beat signal depends on the degree of spread in the clutter and beat signal caused by the radar system phase noise

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.61-68
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• 2019

In addition to non-meteorological echoes, meteorological echoes with large scattering effects, such as precipitation, cause errors in wind data measured by wind profiler. In the rainfall situation, the Doppler spectrum of wind profiler shows both the rainfall signal and the atmospheric signal as two peaks. The vertical radial velocity is very large due to the falling rain drop. The radial velocity contaminated by rainfall decreases the accuracy of the horizontal wind vector and leads to inaccurate weather analysis. In this study, we developed an algorithm to process raw data of wind profiler and distinguished rainfall signal and wind signal by partitioning bimodal peak for Doppler spectrum in rainfall environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1041-1048
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• 2023

Wind LiDAR and Wind Profiler are devices that produce continuous vertical distribution of wind vector in high-resolution data, and their use has recently been increasing. Although the observation and data processing methods of the two devices are similar, differences in wind detection accuracy may occur depending on weather and operation settings. introduce the characteristics of the two instruments and wind calculation methods, and apply the latest instrument verification standards to evaluate their accuracy by comparing them with the wind observed with a radiosonde. Accordingly, a new direction for performance verification following the introduction of equipment and additional necessary complements are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.758-761
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• 2009

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sending purpose such as detection of moving targets and weather surveillance. The signal amplitude in the given frequency band is the important parameter in the detection and tracking of targets. However, the system performance can be seriously degraded if the efficient removal of the strong clutter is not possible. If the phase noise spreads both the signal and clutter, the clutter removal can be very difficult and the accuracy of frequency estimates is also deteriorated. Therefore, in this paper, the effects of phase noise are analyzed in the estimation of beat frequencies.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.393-398
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• 2022

During the test operation period of the wind profiler prototype, radio frequency interference (RFI) contamination occurred in the spectrum. The reference of the RFI that removed the algorithm appearing in the wind profiler spectrum were investigated, and a new algorithm was developed to remove the RFI. First, it was filtered with a threshold value of 0.1 m/s of the spectral width, and the range of the number of gates with the same radial velocity was determined according to whether the beam was a vertical beam or an oblique beam. RFI contamination was removed through filtering and scanning of non-weather signals, and the continuity of wind vectors calculated from the improved spectral radial velocity was verified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.88-92
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• 1985

The performance of MTI signal processors against composite clutter depends not only on the power density functions of the clutter spectrum, but also on the average radar cross sections and the average doppler frequencies of each clutter. In this paper the effect of composite clutter composed of different kinds of clutter such as ground and weather on the MTI signal processors, is compared in terms of MTI improvement factors and the method of comparison is provided.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.141-146
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• 2018

The Ground Moving Target Indication(GMTI) technique can detect the moving targets on land using its Doppler returns. Also, the GMTI system can work in night regardless of the weather condition because it is an active sensor that uses the electromagnetic waves as its source. In order to develop the GMTI system, Constant False Alarm Rate(CFAR) threshold optimization is important because the main performances like detection probability, false alarm rate and Minimum Detectable Velocity(MDV) are related deeply with CFAR threshold. These key variables are used to calculate CFAR threshold and then trade-off between the variables is performed. In this paper, CFAR threshold optimization procedures are introduced, and the optimization results are demonstrated.