• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.1 s.307
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• pp.31-38
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• 2006

In this paper, we consider one-step-ahead control of waveform parameters (pulse amplitudes and lengths, and FM sweep rate) as well as detection thresholds for optimal range and range-rate tracking in clutter. The optimal control of the combined parameter set minimizes a tracking performance index under a set of parameter constraints. The performance index includes the probability of track loss and a function of estimation error covariances. The track loss probability and the error covariance are predicted using a hybrid conditional average algorithm The effect of the false alarms and clutter interference is taken into account in the prediction. Tracking performance of the one-step-ahead control is presented for several examples and compared with a control strategy heuristically derived from a finite horizon optimization.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.333-340
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• 2003

Doppler processing is the heart of pulsed Doppler radar. It gives a clutter elimination and coherent integration. With the improvement of digital signal processors (DPSs), the implementation using them is more widely used in radar systems. Generally, so as for Doppler processor to process the input data in real time, a parallel processing concept using multiple DSPs should be used. This paper implements a programmable Doppler processor, which consists of MTI filter, DFB and square-law detector, using 8 ADSP21060s. Formulating the distribution time of the input data, the transfer time of the output data and the time required to compute each algorithm, it estimates total processing time and the number of required DSP. Finally, using the TSG that provides radar control pulses and simulated target signals, performances of the implemented Doppler processor are evaluated.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.715-721
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• 2012

A threat evaluation is the technique which decides order of priority about tracks engaging with enemy by recognizing battlefield situation and making it efficient decision making. That is, in battle situation of multiple target it makes expeditious decision making and then aims at minimizing asset's damage and maximizing attack to targets. Threat value computation used in threat evaluation is calculated by sensor data which generated in battle space. Because Battle situation is unpredictable and there are various possibilities generating potential events, the damage or loss of data can make confuse decision making. Therefore, in this paper we suggest that substantial threat value calculation using learning bayesian network which makes it adapt to the varying battle situation to gain reliable results under given incomplete data and then verify this system's performance.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.33-38
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• 2018

This paper introduces the simulation concepts and technical approach of wire-guided torpedo performance analysis simulator, as a consequence, provide a framework for understanding overall attack procedures and effectiveness of tactics to torpedo operator. It described the mathematical models of simulation components and weapon engagement principle, especially it derived the closed-form solution of time consumption and leading angle problem of torpedo attack situation based on geographical assumption. In addition, it adopted the proportional navigation guidance at final stage of torpedo attack and also consider the tradeoff relation between target ship speed(propeller noise level) and detection probability, so that it improves the fidelity of physical realism. Simulator is developed with high degree of freedom in the perspective of tactical situation, and it helps user to understand the overall situation and tactical effectiveness.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.487-497
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• 2019

It is very difficult to detect ballistic missiles because of small cross-sections of the radar and the high maneuverability of the missiles. In addition, it is very difficult to recognize and intercept warheads because of the existence of debris and decoy with similar motion parameters in each flight phase. Therefore, feature vectors based on the maneuver, the micro-motion according to flight phase are needed, and the two types of features must be fused for the efficient recognition of ballistic warhead regardless of the flight phase. In this paper, we introduce feature vectors appropriate for each flight phase and an effective method to fuse them at the feature vector-level and classifier-level. According to the classification simulations using the radar signals predicted by the CAD models, the closer the warhead was to the final destination, the more improved was the classification performance. This was achieved by the classifier-level fusion, regardless of the flight phase in a noisy environment.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.109-115
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• 2019

The probability of lethality of personnel targets inside a room is a key issue at assessing effectiveness of a weapon system. In this study, the minimum charge weight to achieve 100% lethality of personnel targets inside a box-type room is proposed at each side length of a base of a room. A fast running blast wave model is used to simulate the pressure-time histories of the blast generated by an internal explosion inside a room, and Axelsson SP method is used to evaluate the lethality of personnel targets under the blast. 176 different internal explosion scenarios are simulated for cases of TNT weights ranging from 20kg to 170kg inside a room whose square base has a side length ranging from 5m to 15m. A linear model and a charge-density model were developed to predict the minimum charge weight to achieve 100% lethality inside a room given a length of a base of a room.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.365-373
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• 2019

An Image Infra-Red(IIR) seeker is widely used for precision guided munitions to provide intelligent and precise target detection in terms of high kill probability. However, there have been issues in determining the performance versus cost trade-offs due to high cost of seeker comparing to other units of the munitions. In this paper, performance/cost evaluations have been carried out to find the most cost-effective solution for developing the IIR seekers. The relationships between the critical parameters and cost are investigated to determine the optimal point which represents the low cost with high performance. It is expected that the presented approach will be able to be used for guidelines to select the appropriate IIR seeker for the given operating conditions and can be useful to estimate the cost effectiveness of the precision guided munitions at early design stage.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.217-222
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• 2021

EOTS(Electro-Optical Tracking System) is utilized in acquiring visual information to assess a guided missile's performance. As the missile travels so fast, it is almost impossible for operator to re-capture the lost target. The RADAR or telemetry data are used to re-capture the lost target however facilities to receive real time data is required, which constrains selection of tracking site. Unlike aforementioned data, pre-calculated nominal trajectory can be used without communication facility. This paper proposes a method to predict lost target's state by employing nominal trajectory. Firstly, observed trajectory and nominal trajectory are compared using DTW and current target's state is predicted. The predicted state is used as observation in Kalman filter's correction phase to predict target's next state. The plausibility of the proposed method is verified by applying on actual missile trajectory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.189-192
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• 2021

This study applies a deep learning-based long short-term memory(LSTM) model to track tracking technology. In the case of existing track tracking technology, the weight of constant velocity, constant acceleration, stiff turn, and circular(3D) flight is automatically changed when tracking track in real time using LMIPDA based on Kalman filter according to flight characteristics of an aircraft such as constant velocity, constant acceleration, stiff turn, and circular(3D) flight. In this process, it is necessary to improve performance of changing flight characteristic weight, because changing flight characteristics such as stiff turn flight during constant velocity flight could incur the loss of track and decreasing of the tracking performance. This study is for improving track tracking performance by predicting the change of flight characteristics in advance and changing flight characteristic weigh rapidly. To get this result, this study makes deep learning-based Long Short-Term Memory(LSTM) model study the plot and target of simulator applied with radar error model, and compares the flight tracking results of using Kalman filter with those of deep learning-based Long Short-Term memory(LSTM) model.