• Title/Summary/Keyword: weather signal

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Development of Simulation Method of Doppler Power Spectrum and Raw Time Series Signal Using Average Moments of Radar Wind Profiler (윈드프로파일러의 평균모멘트 값을 이용한 도플러 파워 스펙트럼 및 시계열 원시신호 시뮬레이션기법 개발)

  • Lee, Sang-Yun;Lee, Gyu-Won
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1037-1044
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    • 2020
  • Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

Advancements in Drone Detection Radar for Cyber Electronic Warfare (사이버전자전에서의 드론 탐지 레이다 운용 발전 방안 연구)

  • Junseob Kim;Sunghwan Cho;Pokki Park;Sangjun Park;Wonwoo Lee
    • Convergence Security Journal
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    • v.23 no.3
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    • pp.73-81
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    • 2023
  • The progress in science and technology has widened the scope of the battlefield, leading to the emergence of cyber electronic warfare that exploits electromagnetic waves and networks. Drones have become more important due to advancements in battery technology and navigation systems. Nevertheless, tackling drone threats comes with its own set of difficulties. Radar plays a vital role in detecting drones, offering long-range capabilities and independence from weather conditions. However, the battlefield presents unique challenges like dealing with high levels of signal noise and ensuring the safety of the detection assets. This paper proposes various approaches to improve the operation of drone detection radar in cyber electronic warfare, with a focus on enhancing signal processing techniques, utilizing low probability of interception (LPI) radar, and implementing optimized deployment strategies.

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

  • Yoo, Yun-Ja
    • Journal of Navigation and Port Research
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    • v.40 no.5
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    • pp.265-270
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    • 2016
  • Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

IGRINS Exposure Time Calculator

  • Le, Huynh Anh Nguyen;Pak, Soojong;Sim, Chae Kyung;Jaffe, Daniel T.
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.62.1-62.1
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    • 2013
  • We present the Exposure Time Calculator of IGRINS (Immersion Grating Infrared Spectrograph). The noises of IGRINS and the simulated emission line can be calculated from the combination of Telluric background emission and absorptions, the emission and transmission of the telescope and instrument optics, and the dark noise and the read noise of the infrared arrays. For the atmospheric transmissions, we apply the simulated spectra depending on the Precipitable Water Vapor (PWV) values. In case of calculation of noises, the user needs to input the expected target magnitude, the weather conditions, and the desired exposure time. In addition to the simulated emission line, the parameters of rest wavelength, line-flux, Doppler shift and line-width are needed. The output would be the expected signal-to-noise for each spectral resolution element. The source-code of IGRINS-ETC v2.1.1 is available to be downloaded on the World Wide Web.

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Quality Analysis of SAR Image

  • Lee, Young-Ran;Kwak, Sung-Hee;Shin, Dong-Seok;Park, Won-Kyu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.628-630
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    • 2003
  • Synthetic Aperture Radar(SAR) is an active microwave instrument that performs high-resolution observation under almost all weather condition. Research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. In fact, many complicated steps are involved in order to generate a SAR image product. The purpose of this paper is to derive quality assessment procedures and define important test parameters in each procedure inside a SAR processor. Thus those test parameter values indicate the quality of SAR image products and verify the processor's performance. Moreover, required procedures to correct and handle errors which are indicated during the assessment are also presented.

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Self-adaptive Online Sequential Learning Radial Basis Function Classifier Using Multi-variable Normal Distribution Function

  • Dong, Keming;Kim, Hyoung-Joong;Suresh, Sundaram
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.382-386
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    • 2009
  • Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

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An Implementation of Traffic Accident Detection System at Intersection based on Image and Sound (영상과 음향 기반의 교차로내 교통사고 검지시스템의 구현)

  • 김영욱;권대길;박기현;이경복;한민홍;이형석
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.6
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    • pp.501-509
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    • 2004
  • The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

DC Langmuir Probe for Measurement of Space Plasma: A Brief Review

  • Oyama, Koichiro
    • Journal of Astronomy and Space Sciences
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    • v.32 no.3
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    • pp.167-180
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    • 2015
  • Herein, we discuss the in situ measurement of the electron temperature in the ionosphere/plasmasphere by means of DC Langmuir probes. Major instruments which have been reported are a conventional DC Langmuir probe, whose probe voltage is swept; a pulsed probe, which uses pulsed bias voltage; a rectification probe, which uses sinusoidal signal; and a resonance cone probe, which uses radio wave propagation. The content reviews past observations made with the instruments above. We also discuss technical factors that should be taken into account for reliable measurement, such as problems related to the contamination of electrodes and the satellite surface. Finally, we discuss research topics to be studied in the near future.

IGRINS Exposure Time Calculator

  • Le, Huynh Anh Nguyen;Pak, Soo-Jong;Kang, Won-Seok;Lee, Jong-Min;Lee, Sung-Won;Seifahrt, Andreas;Jaffe, Daniel T.
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.151.1-151.1
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    • 2011
  • We present the Exposure Time Calculator of IGRINS. The noises of IGRINS can be calculated from the combination of Telluric background emission and absorptions, the emission and transmission of the telescope and instrument optics, and the dark noise and the read noise of the infrared arrays. For the atmospheric transmissions, we apply the simulated spectra depending on the Precipitable Water Vapor (PWV) values. The user needs to input the expected target magnitude, the weather conditions, and the desired exposure time. The output would be the expected signal-to-noise for each spectral resolution element.

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Optimized Station to Estimate Atmospheric Integrated Water Vapor Levels Using GNSS Signals and Meteorology Parameters

  • Beldjilali, Bilal;Benadda, Belkacem
    • ETRI Journal
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    • v.38 no.6
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    • pp.1172-1178
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    • 2016
  • The atmospheric meteorology parameters of the earth, such as temperature, pressure, and humidity, strongly influence the propagation of signals in Global Navigation Satellite Systems (GNSSs). The propagation delays associated with GNSS signals can be modeled and explained based on the atmospheric temperature, pressure, and humidity, as well as the locations of the satellites and receivers. In this paper, we propose an optimized and simplified low cost GNSS base weather station that can be used to provide a global estimate of the integrated water vapor value. Our algorithm can be used to measure the zenith tropospheric delay based on the measured propagation delays in the received signals. We also present the results of the data measurements performed at our station located in the Tlemcen region of Algeria.