• Title/Summary/Keyword: Complex Radar Signal

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Optimal equivalent-time sampling for periodic complex signals with digital down-conversion

  • Kyung-Won Kim;Heon-Kook Kwon;Myung-Don Kim
    • ETRI Journal
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    • v.46 no.2
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    • pp.238-249
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    • 2024
  • Equivalent-time sampling can improve measurement or sensing systems because it enables a broader frequency band and higher delay resolution for periodic signals with lower sampling rates than a Nyquist receiver. Meanwhile, a digital down-conversion (DDC) technique can be implemented using a straightforward radio frequency (RF) circuit. It avoids timing skew and in-phase/quadrature gain imbalance instead of requiring a high-speed analog-to-digital converter to sample an intermediate frequency (IF) signal. Therefore, when equivalent-time sampling and DDC techniques are combined, a significant synergy can be achieved. This study provides a parameter design methodology for optimal equivalent-time sampling using DDC.

A study on the sequential algorithm for simultaneous estimation of TDOA and FDOA (TDOA/FDOA 동시 추정을 위한 순차적 알고리즘에 관한 연구)

  • 김창성;김중규
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.7
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    • pp.72-85
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    • 1998
  • In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.

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Subsidence Measurements of Reclaimed Coastal Land using Satellite Radar Interferometry (위성 레이더 인터훼로메트리를 이용한 연안 매립지의 지반침하량 측정)

  • Kim, Sang-Wan;Won, Joong-Sun
    • Proceedings of the Korean Geotechical Society Conference
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    • 2004.03b
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    • pp.219-226
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    • 2004
  • We measure subsidences occurred in a reclaimed coastal land, Noksan industrial complex, by using JERS-1 SAR (1996-1998) and RADARSAT-1 SAR (2002-2003) dataset. SAR with a high spatial resolution (about several or several tens meter) can reveal the two-dimensional distribution of settlement that would be bardly estimated from in situ measurements. The DInSAR results show significant deformation signal associated with soil consolidation. Accuracy of the settlements estimated by 2-pass differential interferometry (DInSAR) is evaluated using the measurements of settlement gauge. A two-dimensional subsidence map is constructed from 7 qualified pairs. Comparing the JERS-1 radar measurements with the ground truth data yields the correlation coefficient of 0.87 (RMSE of 1.44 cm). The regression line shows the gradient of 1.04 and intercepts close to the origin, which implies that the unbiased settlement can be measured by DInSAR technique. The residual settlements are also detected from RADARSAT-1 pairs. The extent and amount of the settlements are matched well with ground truth data.

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Numerical Modeling for the Identification of Fouling Layer in Track Ballast Ground (자갈도상 지반에서의 파울링층 식별을 위한 수치해석연구)

  • Go, Gyu-Hyun;Lee, Sung-Jin
    • Journal of the Korean Geotechnical Society
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    • v.37 no.9
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    • pp.13-24
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    • 2021
  • Recently, attempts have been made to detect fouling patterns in the ground using Ground Penetrating Radar (GPR) during the maintenance of gravel ballast railway tracks. However, dealing with GPR signal data obtained with a large amount of noise in a site where complex ground conditions are mixed, often depends on the experience of experts, and there are many difficulties in precise analysis. Therefore, in this study, a numerical modeling technique that can quantitatively simulate the GPR signal characteristics according to the degree of fouling of the gravel ballast material was proposed using python-based open-source code gprMax and RSA (Random sequential Absorption) algorithm. To confirm the accuracy of the simulation model, model tests were manufactured and the results were compared to each other. In addition, the identification of the fouling layer in the model test and analysis by various test conditions was evaluated and the results were analyzed.

Fast Preprocessing Technique based on High-Pass Filtering for Spool Rate Extraction of Weak JEM Signals (약한 제트 엔진 변조 신호의 Spool Rate 추출을 위한 High-Pass Filtering 기반의 빠른 전처리 기법)

  • Song, Won-Young;Kim, Hyung-Ju;Kim, Sung-Tai;Shin, In-Seon;Myung, Noh-Hoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.5
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    • pp.380-388
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    • 2019
  • Jet engine modulation(JEM) signals are widely used for target recognition. These signals coming from a potentially hostile aircraft provide specific information about the jet engine. In order to obtain the number of blades, which is uniquely provided by the JEM signal, one must extract the spool rate, which is the rotation speed of the blades. In this paper, we propose an algorithm to extract the spool rate from a weak JEM signal. A criterion is developed to extract the spool rate from the JEM signal by analyzing the intensity of the JEM signal component. The weak signal is first subjected to a high-pass filtering-based process, which modifies it to facilitate spool rate extraction. We then apply a peak detection process and extract the spool rate. The technique is simpler than the existing CEMD or WD method, is accurate, and greatly reduces the time required.

3D Object Modeling for Laser Radar Simulation (레이저레이더 시뮬레이션을 위한 3차원 객체 모델링)

  • Kim, Geun-Han;Jun, Chul-Min
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.2
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    • pp.57-65
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    • 2008
  • The improvement of the performance in laser radar simulation requires fast retrievals of the spatial locations and attributes of objects in response to the laser signals of the simulators. Since the data used in simulation are complex 3D objects such as terrain, buildings and vehicles, and are of large sizes, commonly used 3D modeling tools are not suitable for this use. We proposed a method to store such 3D objects in a database, perform required queries and integrate with visualization tools. We showed the processes for the data modeling based on 3D topological concepts and then building a spatial DBMS. Also, we illustrated the process for accessing and visualizing the stored data using VRML and performed test computations using some laser signal data. With further enhancement on data modeling and LOD problems in visualization, the proposed method will be practically applied in different situations including laser simulation.

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Deinterleaving the Pulse Trains in Multiple Signal Environment (다중 신호환경하에서 펄스 열 분리(deinterleaving))

  • 이성호;김정호;정회인
    • Journal of the Korea Institute of Military Science and Technology
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    • v.5 no.4
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    • pp.38-48
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    • 2002
  • Some signals, such as in radar system, are transmitted as periodic pulse trains. If more than one pulse train are transmitted over the same communication channel, a problem is to separate them for source identification and extract each pulse train at the receiver. This is known as pulse train deinterleaving. In this paper, we present an approach for deinterleaving the pulse trains and extracting their periods combining the estimation of the frequency of each pulse train by DFT, CDIF/SDIF histogram and Sequence Search technique. Also, we present the result of deinterleaving pulse trains and extracting PRI in the complex environment which multiple signals are interleaved.