• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.315-321
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• 2023

In this paper, we propose an algorithm that jointly estimates the location and velocity of a near-field moving target in a pulse radar system. The proposed algorithm estimates the location and velocity corresponding to the outcome of orthogonal matching pursuit (OMP) in a 4-dimensional (4D) location-velocity space. To address the high computational complexity of 4D parameter joint estimation, we propose an algorithm that iteratively estimates the target's 2D location and velocity sequentially. Through simulations, we analyze the estimation performance and verify the computational efficiency of the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.4
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• pp.92-98
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• 2002

In this study, maximum launch range and F-pole are evaluated and analyzed for the semi-active radar missile concerning various launch condition, performance limitation and target maneuvers. Furthermore, general evasion maneuvers are considered when shooter approaches to target with head-on conditions. A point-mass target, shooter and missile model is used including aircraft and missile dynamics. More realistic missile motion simulation is conducted using aerodynamic performance data, geometry, performance limitation, radar seeker performance and so on. Maximum launch range, which is the distance for intercept satisfying target and missile motion and performance, is evaluated using root finding method. F-pole, which is the distance between target and shooter when intercept is completed, is evaluated assuming that shooter maneuvers through pursuit guidance to target.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.198-206
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• 2013

This paper presents the improvement of tracking performance using fuzzy inference system based task prioritizations for multi-function radars. The presented technique calculates elemental priorities using track information of a target and obtain the total priority from fuzzy inference system of each fuzzy set's membership function. In this paper, we proposed the task prioritization algorithms based on fuzzy inference system, and evaluated the tracking performance on multi-function radar scenario using it. As a result, we confirmed that excellent performance could be achieved when using the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.669-676
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• 2016

North Korea has various ballistic missiles from short range to long range such as inter continental ballistic missiles. Short range ballistic missiles such as SCUD series are threatening to Korea peninsula. Therefore Korea is constructing various missile defense systems to protect country. Parameters influencing the received power from the target to the radar are transmitting power, antenna gain, carrier frequency, RCS(Radar Cross Section) of target and distance from radar to target. Especially, RCS and distance from target are not radar performance defined parameters but external parameters. Therefore radar deployment position that large RCS can be observed and target to radar distance should be considered in parallel to improve target detection probability. In this paper, RCS pattern of SCUD-B ballistic missile is calculated, received power is analyzed based on radar deployment position during ballistic missile trajectory and methode for optimum radar deployment position to improve target detection probability is suggested.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.239-250
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• 2022

In this paper, we analyze the performance of an FM radio based passive radar in the presence of deception jamming such as false-target generation. To do this, we examine the effects of applying the deception jamming signal to the passive radar through the derivation of the construction of the amplitude-range-Doppler(ARD) plot. The analysis results show that applying the deception jamming signal with the low power similar to the target echo signal generates false targets at positions set by the jamming variables compared to the real target position in the ARD plot. Also, it is possible to induce the jamming effect so that only false targets are detected by selecting appropriate jamming power. Simulations are included to verify the theoretical results and to discuss on the effectiveness of the deception jamming on the FM radio based passive radar.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2002.11a
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• pp.196-199
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• 2002

In this paper, variable threshold estimation algorithm for multiple vehicle detection RADAR is proposed and realized by using DSP for real time processing. The algorithm is developed to get the information of velocity and length of vehicles in multiple lanes by using FMCW RADAR. For real time operation, signal processing part is realized with a high speed DSP board to detect and manipulate the vehicle data and some experimental results are given to show the usefulness of the proposed technique.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.71-77
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• 2017

This paper proposes a low complexity frequency modulated continuous wave (FMCW) surveillance radar algorithm. In the conventional surveillance radar systems, the two dimensional (2D) fast Fourier transform (FFT) method is usually employed in order to detect the distance and velocity of the targets. However, in a surveillance radar systems, it is more important to immediately detect the presence or absence of the targets, rather than accurately detecting the distance or speed information of the target. In the proposed algorithm, in order to immediately detect the presence or absence of targets, 1D FFT is performed on the first and M-th bit signals among a total of M beat signals and then a phase change between two FFT outputs is observed. The range of target is estimated only when the phase change occurs. By doing so, the proposed algorithm achieves a significantly lower complexity compared to the conventional surveillance scheme using 2D FFT. In addition, show in order to verify the performance of the proposed algorithm, the simulation and the experiment results are performed using 24GHz FMCW radar module.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.640-647
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• 2018

This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.711-720
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• 2015

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance have been reported. Since several pixels per an object may be generated in a close-range radar application, a width of an object can be estimated automatically by various signal processing techniques. In this paper, we tried to attempt to develop an algorithm to estimate obstacle width using Radar images. The proposed method consists of 5 steps - 1) background clutter reduction, 2) local peak pixel detection, 3) region growing, 4) contour extraction and 5)width calculation. For the performance validation of our method, we performed the test width estimation using a real data of two cars acquired by commercial radar system - I200 manufactured by Navtech. As a result, we verified that the proposed method can estimate the widths of targets.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.633-642
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• 2016

It is important for advanced active safety systems and autonomous driving cars to get the accurate estimates of the nearby vehicles in order to increase their safety and performance. This paper proposes a sensor fusion method for radar and vision sensors to accurately estimate the state of the preceding vehicles. In particular, we performed a study on compensating for the lateral state error on automotive radar sensors by using a vision sensor. The proposed method is based on the Interactive Multiple Model(IMM) algorithm, which stochastically integrates the multiple Kalman Filters with the multiple models depending on lateral-compensation mode and radar-single sensor mode. In addition, a Probabilistic Data Association Filter(PDAF) is utilized as a data association method to improve the reliability of the estimates under a cluttered radar environment. A two-step correction method is used in the Kalman filter, which efficiently associates both the radar and vision measurements into single state estimates. Finally, the proposed method is validated through off-line simulations using measurements obtained from a field test in an actual road environment.