• Title/Summary/Keyword: Radar Bias

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Estimation of Launch Vehicle Tracking Error due to Radio Refraction (레이다 전파굴절에 의한 발사체 추적오차 추정)

  • Seo, Gwang-Gyo;Kim, Yoonsoo;Shin, Vladimir;Song, Ha-Ryong;Choi, Yong-Tae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.45 no.12
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    • pp.1076-1083
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    • 2017
  • This paper discusses the error estimation in radar measurement data obtained while tracking a launch vehicle. It is known that typical radar measurement data consist of the true positional or orientation information on the vehicle being tracked, random noise and a deterministic bias due to radio refraction. Unlike previous research works, this paper proposes a tracking-error (mainly bias) estimation method solely based on the single radar measurement with no aid of other measurement such as GPS. The proposed method has been verified with real measurement data obtained while tracking the KSLV-I launch vehicle.

Joint Range and Angle Estimation of FMCW MIMO Radar (FMCW MIMO 레이다를 이용한 거리-각도 동시 추정 기법)

  • Kim, Junghoon;Song, Sungchan;Chun, Joohwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.2
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    • pp.169-172
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    • 2019
  • Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

Design of Temperature Compensation Circuit for W-band Radar Receiver (W-band 레이더 수신기용 온도보상회로 설계)

  • Lee, Dongju;Kim, Wansik;Kwon, Jun-Beom;Seo, Mihui;Kim, Sosu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.4
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    • pp.129-133
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    • 2020
  • In this paper, a temperature compensation circuit is presented in order to mitigate gain variability due to temperature in the W-band low-noise amplifier (LNA). The proposed cascode temperature compensation bias circuit automatically controls gate bias voltages of the common-source LNA in order to suppress variations of small-signal gain. The designed circuit was realized in a 100-nm GaAs pHEMT process. The simulated voltage gain of W-band LNA including the proposed bias circuit is >20 dB with gain variability less than ±0.8 dB in the range of temperatures between -35 to 71℃. We expect that the proposed circuit contributes to millimeter-wave receivers for stable performances in radar applications.

ERS-1 AND CCRS C-SAR Data Integration For Look Direction Bias Correction Using Wavelet Transform

  • Won, J.S.;Moon, Woo-Il M.;Singhroy, Vern;Lowman, Paul-D.Jr.
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.49-62
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    • 1994
  • Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

Preliminary Analysis of Data Quality and Cloud Statistics from Ka-Band Cloud Radar (Ka-밴드 구름레이더 자료품질 및 구름통계 기초연구)

  • Ye, Bo-Young;Lee, GyuWon;Kwon, Soohyun;Lee, Ho-Woo;Ha, Jong-Chul;Kim, Yeon-Hee
    • 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.

Effect of R-Z Relationships Derived from Disdrometer Data on Radar Rainfall Estimation during the Heavy Rain Event on 5 July 2005 (2005년 7월 5일 폭우 사례 시 우적계 R-Z 관계식이 레이더 강우 추정에 미치는 영향)

  • Lee, GyuWon;Kwon, Byung-Huk
    • Journal of the Korean earth science society
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    • v.33 no.7
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    • pp.596-607
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    • 2012
  • The R-Z relationship is one of important error factors to determine the accuracy of radar rainfall estimation. In this study, we have explored the effect of the R-Z relationships derived from disdrometer data in estimating the radar rainfall. The heavy rain event that produced flooding in St-Remi, Quebec, Canada has been occurred. We have tried to investigate the severity of rain for this event using high temporal (2.5 min) and spatial resolution ($1^{\circ}$ by 250 m) radar data obtained from the McGill S-band radar. Radar data revealed that the heavy rain cells pass directly over St-Remi while the coarse raingauge network was not sufficient to detect this rain event. The maximum 30 min (1 h) accumulation reaches about 39 (42) mm in St-Remi. During the rain event, the two disdrometers (POSS; Precipitation Occurrence Sensor System) were available: One used for the reflectivity calibration by comparing disdrometer Z and radar Z and the other for deriving disdrometric R-Z relationships. The result shows the significant improvement with the disdrometric reflectivity-dependent R-Z relationships against the climatological R-Z relationship. The bias in radar rain estimation is reduced from +12% to -2% and the root-mean squared error from 16 to 10% for daily accumulation. Using the estimated radar rainfall rate with disdrometric R-Z relationships, the flood event was well captured with proper timing and amount.

On the Correction of Mean-Field Bias of Radar Rainfall Using Spatially Disproportionate Rain Gauge Network: A Case Study of Ganghwa Rain Radar in Korea (지역적으로 편중된 우량계 자료를 이용한 레이더 강우의 편의 보정: 강화 수문레이더의 사례 연구)

  • Yoo, Chul-Sang;Kim, Byoung-Soo;Yoon, Jung-Soo;Ha, Eun-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.284-288
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    • 2008
  • 레이더 강우의 편의 추정은 근본적으로 레이더 강우의 평균과 참값으로 가정되는 우량계 강우의 평균과의 차이를 결정하는 문제이다. 두 관측치의 차이를 정확히 결정하기 위해서는 두 관측치의 차이에 대한 분산이 매우 작아야 하며, 따라서 비교되는 관측치의 수가 충분히 확보되어야 한다. 즉, 이 문제는 두 관측치의 차이에 대한 분산의 규모를 주어진 조건에 맞추기 위해 필요한 우량계의 수를 결정하는 것이 된다. 본 연구에는 특히 일부 지역에만 우량계의 설치가 가능한 경우를 대상으로 하고자 한다. 이는 임진강 유역에 대해 강우레이더를 운영하는 경우에 해당하는 문제이며, 또한 바다와 접한 지역에서 레이더를 설치 운영할 경우에도 발생하는 문제이다. 본 연구에서는 임진강 유역을 대상으로 하였으며, 전체 유역의 약 1/3정도인 하류유역에서만 우량계 자료가 가용한 경우와 전체 유역에 대해 우량계 강우가 가용한 경우의 차이를 비교하였다. 이러한 분석결과를 토대로 임진강 유역 전체 지역에 고르게 우량계가 분포할 경우의 관측정도를 얻기 위한 하류유역의 우량계 밀도를 제시하였다.

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Off-grid direction-of-arrival estimation for wideband noncircular sources

  • Xiaoyu Zhang;Haihong Tao;Ziye, Fang;Jian Xie
    • ETRI Journal
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    • v.45 no.3
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    • pp.492-504
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    • 2023
  • Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer-Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.

A Study on Improving Mass Production of the Radar Sensor Oscillator (레이더 센서용 발진기의 양산성 향상에 관한 연구)

  • Kim, Byung-Chul;Cho, Kyung-Rae;Lee, Jae-Buom;Kim, Dae-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.4
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    • pp.669-676
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    • 2012
  • In this paper, The method to improve the mass production method of the radar sensor is suggested by using the temperature compensation circuit which is composed with the thermister. The mass production became easier by decreasing the adjustment time for the exact oscillation frequency with the temperature compensation circuit that can support the proper gate bias voltage for the FET after the dielectric resonator is removed from the DRO(Dielectric Resonator Oscillator) of the radar sensor. Radar sensor with the proposed method has 15.67MHz oscillator frequency variation in the temperature range of $-20^{\circ}C-+55^{\circ}C$, 0.65dB magnitude variation, -105.47dBc phase noise characteristics at 1MHz which are better or similar temperature characteristics with the DRO whose oscillator frequency variation is 25MHz, magnitude variation is 0.42dB and phase noise is -107.40dBc in the same temperature range.

Improvement of KOMPSAT-5 Sea Surface Wind with Correction Equation Retrieval and Application of Backscattering Coefficient (KOMPSAT-5 후방산란계수의 보정식 산출 및 적용을 통한 해상풍 산출 결과 개선)

  • Jang, Jae-Cheol;Park, Kyung-Ae;Yang, Dochul;Lee, Sun-Gu
    • 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.