• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.54-65
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• 2007

Parameter optimization technique is applied to planning UAVs(Unmanned Aerial Vehicles) path under artificial enemy radar threats. The ground enemy radar threats are characterized in terms of RCS(Radar Cross Section) parameter which is a measure of exposure to the radar threats. Mathematical model of the RCS parameter is constructed by a simple mathematical function in the three-dimensional space. The RCS model is directly linked to the UAVs attitude angles in generating a desired trajectory by reducing the RCS parameter. The RCS parameter is explicitly included in a performance index for optimization. The resultant UAVs trajectory satisfies geometrical boundary conditions while minimizing a weighted combination of the flight time and the measure of ground radar threat expressed in RCS.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.332-340
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• 2019

Electronic warfare systems are needed to be advantageous in the modern war. Many radar threat signals with various frequency spectrums and complicated techniques exist. For detecting the threats, a receiver with wide and narrow-band digital processing is needed. To process a wide-band searching mode, a polyphase filter bank has become the architecture of choice to efficiently detect threats. A polyphase N-path filter aligns the re-sampled time series in each path, and a discrete Fourier transform aligns phase and separates the sub-channel baseband aliases. Multiple threats and CW are detected or rejected when the signals are received in different sub-channels. And also, to process a narrow-band precision mode, a direct down converter is needed to reduce aliasing by using a decimation filter. These digital logics are designed in a FPGA. This paper shows how to design and develop a wide and narrow-band digital receiver that is capable to detect the threats.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.29-39
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• 2017

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.258-259
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• 2018

The United States has deployed and operates a ballistic missile defense system to defend the homeland from ballistic missile attacks launched from direct and potential threats. The Missile Defense Agency has deployed the Aegis BMDs, Sea-based X-band radars(SBX), Ground-Based Interceptors(GBI), Early Warning Radars and THAADs. In addition, the Homeland Defense Radar-Hawaii(HDR-H) will be deployed in Hawaii. The HDR-H is expected to improve defensive ability to ballistic missile threats in the Asia-Pacific region.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.112-123
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• 2017

Research for the inverse estimation of RF threats and the efficient electronic attack based on the parameters of the electronic information has been active in the electronic warfare (EW) situations. In this paper, an EW transmission simulator is constructed from the modeling of radar threats, EW receivers, and propagation environments with the collected electronic information in order to verify the performance of the inverse estimation algorithm in various and practical EW situations. In simulation results, we show that the range tracking error and angle tracking error are produced within ten meters and one degree, respectively. And also, we show that the changing relations between the angle tracking error and the parameters of the monopulse angle tracking radar such as the beamwidth and squint angle in simulation results correspond with those in the theoretical modeling. Accordingly, the constructed EW simulator can be used to observe the modifying characteristics of the electronic information in transmission environments, and then, to evaluate the performance of the inverse estimation system in various EW situations.

• Journal of Aerospace System Engineering
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• v.15 no.2
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• pp.36-44
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• 2021

Unmanned aerial vehicles (UAVs) are increasingly needed as they can replace manned aircrafts in dangerous military missions. However, because of their low autonomy, current UAVs can execute missions only under continuous operator control. To overcome this limitation, higher autonomy levels of UAVs based on autonomous situational awareness is required. In this paper, we propose an autonomous situational awareness software consisting of situation awareness management, threat recognition, threat identification, and threat space analysis to detect dynamic situational change by external threats. We implemented the proposed software in real mission computer hardware and evaluated the performance of situational awareness toward dynamic radar threats in flight simulations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.147-157
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• 2018

There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.74-80
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• 2006

This paper addresses the trajectory optimization of Unmanned Aerial Vehicles(UAVs) under multiple ground threats like enemy's anti-air radar sites. The power of radar signal reflected by the vehicle and the flight time are considered in the performance cost to be minimized. The bank angle is regarded as control input for a 1st-order lag vehicle, and input parameter optimization method based on Sequential Quadratic Programming (SQP) is used for trajectory optimization. The proposed path planning method provides more practical trajectories with enhanced survivability than those of Voronoi diagram method.