• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1333-1339
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• 2009

A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.

• Journal of electromagnetic engineering and science
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• v.18 no.4
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• pp.231-241
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• 2018

In this paper, we consider the anti-attack procedure of a ballistic missile defense system (BMDS) at different operating frequencies at its phased-array radar station. The interception performance is measured in terms of lateral divert (LD), which denotes the minimum acceleration amount available in an interceptor to compensate for prediction error for a successful intercept. Dependence of the frequency on estimation accuracy that leads directly to prediction error is taken into account, in terms of angular measurement noises. The estimation extraction is performed by means of an extended Kalman filter (EKF), considering two typical re-entry trajectories of a non-maneuvering ballistic missile (BM). The simulation results show better performance at higher frequency for both tracking and intercepting aspects.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.223-229
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• 2017

An angle error is a factor obstructing to track accurate position in tracking radars. And the noise incurring the angle error can be divided as follows; thermal noise and glint. In general, Extended Kalman filter used in tracking radars is designed with considering thermal noise only. The Extended Klaman filter uses a fixed measurement error covariance when updating an estimate state by using ahead state and measurement. But, a noise power varies according to the range. Therefore we purposes the adaptive Kalman filter which changes the measurement noise covariance according to the range. In this paper, we compare the performance of the Extended Kalman filter and the proposed adaptive Kalman filter by considering KSLV-I (Korean Satellite Launch Vehicles).

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.1
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• pp.23-29
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• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• ETRI Journal
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• v.40 no.5
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• pp.592-603
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• 2018

In order to obtain better target identification performance, an efficient waveform design method with high range resolution and low sidelobe level for orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) radar is proposed in this paper. First, the wideband CP-based OFDM signal is transmitted on each antenna to guarantee large bandwidth and high range resolution. Next, a complex orthogonal design (COD) is utilized to achieve code domain orthogonality among antennas, so that the spatial diversity can be obtained in MIMO radar, and only the range sidelobe on the first antenna needs suppressing. Furthermore, sidelobe suppression is expressed as an optimization problem. The integrated sidelobe level (ISL) is adopted to construct the objective function, which is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. The numerical results demonstrate the superiority in performance (high resolution, strict orthogonality, and low sidelobe level) of the proposed method compared to existing algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.639-645
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• 2010

This paper presents the sensor fusion algorithm that recognizes a primary vehicle by fusing radar and monocular vision data. In general, most of commercial radars may lose tracking of the primary vehicle, i.e., the closest preceding vehicle in the same lane, when it stops or goes with other preceding vehicles in the adjacent lane with similar velocity and range. In order to improve the performance degradation of radar, vehicle detection information from vision sensor and path prediction predicted by ego vehicle sensors will be combined for target classification. Then, the target classification will work with probabilistic association filters to track a primary vehicle. Finally the performance of the proposed sensor fusion algorithm is validated using field test data on highway.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.363-372
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• 1993

For more accurate height/depth control of the agricultural implements , the soil surface as a reference position should be measured as accurate as possible. A new measurement system using microwave was developed to detect the true soil surface even under plant and/or vegetation. Two-frequency continuous-wave radar was used as the measurement system. It could estimate the distance to the target by measuring the phase difference between two different frequencies continuous-waves which reflected on the target surface. The system performance was evaluated on the barely field where the average height of barley was 91.5 cm. The experimental results showed that the system performance was not affected by the existence of barely. The maximum measurement errors were 8.91 com and 8.44cm for two different experimental plots.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.810-820
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• 2014

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance are reported. In near field, several hits per an object are generated after signal processing of Radar data. Hence, clustering is an essential technique to estimate their shapes and positions precisely. This paper proposes a method of grouping hits in range-doppler domains into clusters which represent each object, according to the pre-defined rules. The rules are based on the perceptual cues to separate hits by object. The morphological connectedness between hits and the characteristics of SNR distribution of hits are adopted as the perceptual cues for clustering. In various simulations for the performance assessment, the proposed method yielded more effective performance than other techniques.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.208-216
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• 2017

This paper presents the design method of an FMCW(frequency-modulated continuous-wave) altitude simulator which generates propagation delay signals according to target distances to test the radar altimeter. To improve the conventional RF method for creating delay signals, the simulator is designed by the RF-optics-RF method using optical delay lines. In addition, it is designed to simulate the Doppler shift and jamming that may occur in actual flight environment. In order to evaluate the performance of the developed simulator, the integration tests have been conducted with the radar altimeter. Through the test, we successfully verified the performance of the simulator.