• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.67-79
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• 2019

A warship equipped with Multi Function Radar(MFR) performs operations by evaluating the degree of threats based on threats' symptom and allocating the resource of MFR to the corresponding threats. This study suggests a simulation-based approach and greedy algorithm in order to effectively allocate the resource of an MFR for warships, and compares these two approaches. As a detection probability function depending on the amount of allocations to each threat, we consider linear and exponential functions. Experimental results show that both the simulation-based approach and greedy algorithm allocate resource similarly to the randomly generated threats, and the greedy algorithm outperforms the simulation-based approach in terms of computational perspective. For a various cases of threats, we analyze the results of MFR resource allocation using the greedy algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1099-1106
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• 2018

In this paper, we developed and then analyzed the specifications of the frequency synthesizer which was applied to long range MFR (Multi-function Radar). These specifications were able to guarantee the functions and performance of MFR. MFR was the radar system that used phase array for electronically scanning. This frequency synthesizer made various frequency signals including to STALO (Stable Local Oscillator) for MFR. By analyzing the MFR requirements, we choose the optimal frequency synthesis method and then we got the best performance and functionality including to physical size for this system. We designed and fabricated DDS (Direct Digital Synthesizer)-driven Offset-PLL (Phase Locked Loop) synthesizer to meet the requirements which were low phase noise, fast switching time and low spurious. This synthesizer had less than -131dBc/Hz@100kHz phase noise and less than $4.1{\mu}s$ switching time, respectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.517-523
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• 2011

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.1-8
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• 2023

This paper presents the control strategy of Auto-leveling equipment (ALE) of Multi-function radar (MFR) for vehicle using Embedded System. MFR implements surveillance patrol missions such as surface-to-air missiles and fighters with constant rotation. ALE consists of 4 Auto-leveling modules (ALM) and retains the stability with maintaining level. The gradient of vehicle can be measured and controlled by embedded systems. This paper contributes for improvement the system design with the ALM 1 set modeling. The validity of the modeling is verified using MATLAB/Simulink.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.151-159
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• 2022

In this paper, we implement a digital multi-beamformer using FPGA(Field Programmable Gate Array) which has advantages in parallel and real-time data processing. This is accomplished through the use of not only high-speed data communication but also multiple beam forming, which is currently required by MFR(Multi Function Radar). As a result, the beamformer can process 24 Gbps throughput in real-time and form 5 digital beams at the same time. It is also compared to the results of Matlab simulations. We demonstrate how an implemented beamformer can be used in an MFR system by using a digital array antenna.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.507-517
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• 2019

Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.123-131
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• 2020

The system performance of naval multi function radar is affected by radar beam operation. Multi f function radar has to operate complicated beam better than search radar and tracking radar which have single operation. This paper describes fabricating analysis tool for the verification method for system performance of naval multi function radar. We composed the model that naval ship with MFR and radar which are detecting targets to verification the system performance. The targets are composed anti-aircraft and anti-ship. We integrate each model and make naval MFR simulator that applied resource management of track beam and search beam. We verify analysis tool by simulation in operating scenario after adjusting system parameter to analysis tool.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.404-413
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• 2015

The target classification for ballistic target(BT) is one of the most critical issues of ballistic defence mode(BDM) in multi-function radar(MFR). Radar responds to the target according to the result of classifying BT and air breathing target(ABT) on BDM. Since the efficiency and accuracy of the classification is closely related to the capacity of the response to the ballistic missile offense, effective and accurate classification scheme is necessary. Generally, JEM(Jet Engine Modulation), HRR(High Range Resolution) and ISAR(Inverse Synthetic Array Radar) image are used for a target classification, which require specific radar waveform, data base and algorithms. In this paper, the classification method that is applicable to a MFR system in a real environment without specific waveform is proposed. The proposed classifier adopts kinematic data as a feature vector to save radar resources at the radar time and hardware point of view and is implemented by fuzzy logic of which simple implementation makes it possible to apply to the real environment. The performance of the proposed method is verified through measured data of the aircraft and simulated data of the ballistic missile.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.114-122
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• 2020

When replacing hardware due to obsolescence, discontinuation, and expansion of software-equipped electronic equipment, software changes are required in the past, but if virtualization technology is applied, it can be applied without software changes. In this regard, we studied in order to apply virtualization technology in the development of naval multi-function radar signal processing, we studied hardware and OS independency for Docker and performance comparison between Docker and virtual machine. As a result, it was confirmed that hardware and OS independence exist when using Docker and that high-speed processing is possible compared to the virtual machine.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1045-1059
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• 2011

A 3-D multi-function radar(MFR) is a modern radar to provide various target information, such as range, doppler, and angle by performing surveillance, multiple target tracking, and missile guidance. In this paper, we introduced a real-time radar signal processor(RSP), which is a crucial component of MFR with its design, implementation using high-speed multiple DSP, and performance. Additionally, we verified that several advanced signal processing algorithms were well-performed in our RSP, such as MCA-CFAR algorithm for target detection in clutter environment, range and velocity measurement algorithm using discriminator estimation, and noise jammer detection algorithm using local minimum selection.