• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.23-28
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• 2005

An airborne radar is an essential aviation electronic system of the helicopter to perform various missions in all-weather environments. This paper presents the results of the design and implementation of the airborne pulse doppler radar signal processor using high multi-DSP for the multi-function radar capability such as short-range, midium-range, and long-range depending on the mission of the vehicle. Particularly, the radar signal processor is developed using two DSP boards in parallel for the various radar signal processing algorithm. The key algorithms include LFM chirp waveform-based pulse compression, MTI clutter filter, MTD processor, adaptive CFAR, and clutter map. Especially airborne moving clutter Doppler spectrum compensation algorithm such as TACCAR is implemented for the multi-mode airborne radar system. The test results shows the good Doppler spectral separation for the clutter and the moving target in the flight test environment using helicopter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.577-587
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• 2013

In this paper, an integrated radar resource manager for an airborne multi-function radar and a radar-environment simulator are presented. The radar-environment simulator includes target detection/measurement models, a nonlinear tracking filter for the airborne radar and an effective target generation algorithm. The structures and functions of modules in the radar resource manager are established and validated by the radar-environment simulator.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.12
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• pp.976-985
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• 2018

Modern radars such as the phase array radar can handle various tasks by generating a beam from a phased array antenna. Radar can be used for miscellaneous applications such as surveillance, tracking, missile guidance etc. Previous radar systems could handle only one task at a time. As such, multiple radars were required to perform simultaneous tasks. Multi-function radars can perform many tasks using only one radar system. However, the radar's resources are limited in this instance. To efficiently utilize time, it is necessary to properly schedule tasks in the radar's timeline. In this report, we investigate the efficiency of different scheduling tasks.

• Journal of IKEEE
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• v.19 no.3
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• pp.431-439
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• 2015

This paper introduces analysis technique and test procedure for verifying the reliability of the multi-function radar software. Also the process of software development and reliability test method for reducing the development period are described. Test results show that the verified software has reduced errors and improved reliability compared to the unverified software.

• 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.

• 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.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.1-13
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed the several dispatching rules for radar beam scheduling, and compared the performance on the multi-function radar scenario. We also showed that the dispatching rule which differently applying SPF(Shortest Processing time First) and ERF(Earliest Request time First) according to beam processing latency is the most efficient.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.443-446
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• 2005

This paper presents the results of the design and implementation of the airborne pulse doppler radar signal processor using high multi-DSP for the multi-function radar capability such as short-range, midium-range, and long-range depending on the mission of the vehicle. Particularly, the radar signal processor is developed using two DSP boards in parallel for the various radar signal processing algorithm. The key algorithms include LFM chirp waveform-based pulse compression, MTI clutter filter, MTD processor, adaptive CFAR, and clutter map. Especially airborne moving clutter Doppler spectrum compensation algorithm such as TACCAR is implemented for the multi-mode airborne radar system. The test results shows the good Doppler spectral separation for the clutter and the moving target in the flight test environment using helicopter

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.995-1001
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• 2012

This paper compares the performance of several tracking filters, namely, alpha-beta filter, Kalman filter and TBM tracking filter for ballistic target tracking problem using multi-function radar. Every of three tracking filters suggested was tested on simulator developed in accordance with TBM trajectory and MFR RSP measurement. The result shows the method using TBM tracking filter gives 75.3 % decreased velocity RMS error than alpha-beta filter. After initialization, the RMS error of range and velocity of the proposed filter is also smaller than the Kalman filter. Finally the proposed filter is suitable for high-speed TBM tracking due to the stable angle tracking accuracy.