• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.113-118
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• 2009

In this paper, we described the model of noise, target for tracking radar and range tracking, angle tracking, and Doppler frequency tracking for target acquisition and tracking. Target signal as well as the noise signal is modeled as random process varying with elapsed time. This paper addresses three areas of radar target tracking: range tracking, angle tracking, and Doppler frequency tracking. In general, range tracking is prerequisite to and inherent in both angle and Doppler frequency tracking systems. First, we introduced the several range tracking and described techniques for achieving range tracking. Second, we described the radar angle tracking techniques including conical scan, sequential lobing, and monopulse. Finally, we presented concepts and techniques for Doppler frequency tracking for several radar types.

• Aerospace Engineering and Technology
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• v.10 no.1
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• pp.116-121
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• 2011

The tracking radar systems in NARO space center are used in order to acquire the TSPI (Time, Space, and Position Information) data of the launch vehicle. The tracking radar produce the measurements of tracked targets in the radar-centered coordinate system. When the tracking radar is in the Cartesian/Polar tracking mode, the state vector data is sent in radar-centered Cartesian/Polar coordinate system to RCC. RCC also send the slaving data in Test Range coordinate system to the tracking radar. So, the tracking radars have to transform the slaving data in Test Range coordinate system into in radar-centered coordinate system. In this study, we described the coordinate transformation between radar-centered coordinate system and Test Range coordinated system.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.85-92
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• 2008

An architecture for multiple radar tracking systems can be broadly categorized according to the methods in which the tracking functions are performed : central-level tracking and distributed tracking. In the central-level tracking, target tracking is performed using observations from all radar systems. This architecture provides optimal solution to target tracking. In distributed tracking, tracking is performed at each radar system and the composite track information is formed through track fusion integrating multiple radar-level tracks. Track-to-track fusion and track-to-track association are required to perform in this architecture. In this paper, issues and recent research on the two tracking architectures are surveyed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.71-77
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• 2020

Recently, the tracking radar has confirmed the necessity of developing a small tracking radar that can be operated without various restrictions in various environments. In addition, the performance of a small tracking radar requires equal to or higher than the existing tracking radar. Such a small tracking radar can be implemented through miniaturization and low power of existing tracking radar. In this paper, the role and function of a signal processor for a small tracking radar are defined and we proposed a method to increase the efficiency of power consumption and miniaturization by minimizing the use of devices required to implement a signal processor for a small tracking radar. Used as a method for miniaturization, a device processor such as DDC and communication controller was implemented in an FPGA to design a signal processor for a small tracking radar. In addition, a low-power signal processor was designed by a power supply using a highly efficient switching regulator. Finally, the signal processor was verified by the performance test of the signal processor for the small tracking radar implemented, the Doppler tracking test using the signal processor on the small tracking radar, and the distance tracking test.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.23-28
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• 2021

In this paper, we analyze the tracking errors of monopulse radar according to the JSR of retrodirective cross-eye and radar skin return signals. The cross-eye jammer gain(G_c) is used to calculate the radar tracking errors, and the relationship between the jammer gain and the JSR is represented mathematically. We analyze the radar tracking errors by varying the tracking angle and JSR. Analysis results of the phase difference(ϕ) and amplitude ratio(a) between the two jammer signals and the changing JSR show that the closer the phase difference of the two jammer signals is to 180, the greater the tracking error and it shows that if the JSR is above 20dB, the tracking errors no longer increase. This work presents an effective utilization of retrodirective cross-eye jammers through various tracking error analyses based on the JSR, tracking angles, two-jammer phase differences and amplitude ratios of two-jammer signals.

• 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.20 no.3
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• pp.352-361
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• 2017

This paper proposes a design and fabrication of the test equipment that is implemented as a part of the airborne tracking radar inspection under the environment of indoor simulation. This test equipment provides controlling the operation status of airborne tracking radar and replicating the velocity and range information of target by generating a variety of target signal. This is mainly composed of radar operation controller, target signal generator, horn antenna driving devices. Radar operation controller is able to perform the controlling of radar operation mode and monitoring in real time by serial communication. Target signal generator is generated doppler signal and range delayed signal using virtual target of RF-band. Horn antenna driving devices perform a role of target simulating exercise. In the end, the performance is demonstrated using experiment results of test equipment for airborne tracking radar.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.66-74
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• 2012

The virtual target signal generator was developed to verify the shipborne tracking radar performance. It was used to DRFM(Digital RF Memory) method to generate the virtual moving targets. The target signal includes Doppler shift and RCS according to the target motion. And the signal generator can make jamming signal and clutter to test shipborne radar performance at real environmental condition. This paper described the functional diagram and the hardware configuration items to meet the test requirements for the tracking radar. And it showed the critical design points for the sub-systems. The signal generator which was developed in this paper shared the operational information of the radar with the radar command and control part. To test the frequency agility of the radar, it had the local oscillator which could do high speed frequency switching according to radar information. By communicating between the signal generator and the radar command and control part, the local oscillator of signal generator could be controlled every pulse. It reduced the instantaneous bandwidth of signal generator and minimized the spurious. So it lowered the probability of generating wrong targets.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.311-314
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.