• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.117-133
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• 2007

The weapon accuracy is a basic measure of performance in the area of weapon system acquisition. It requires the establishment of correct concept and the T&E methods. Existing T&E method for aircraft weapon systems have not considered types of exact hitting area for various weapons. This study intends to suggest an optimal T&E methods in Korean T&E environment. In order to sampling and to test aircraft weapon accuracy, we need probability and statistic theories. There are many types of CEP(Circular Error Probable) methods. We recommend 2 types of CEP methods which are Lockheed Martin CEP method and Johnson CEP method. Also, suggest some other T&E methods. These methods can be used to accuracy test in the area of weapon system acquisition in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.8
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• pp.741-746
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• 2007

In this paper, we propose an accuracy analysis method for air-to-ground weapon delivery. The lethality, which is one of the most important factor to evaluate combat effectiveness of a fighter, depends on the capability to improve the accuracy of the conventional weapon delivery. We present error elements which affect the error analysis for air-to-ground weapon delivery from the initial design phase to the final validation phase. And we introduce an accuracy analysis method to reflect the error elements and to evaluate them quantitatively. We assume zero bias-error and consider random error for the weapon delivery accuracy analysis.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.59-67
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• 2011

This paper proposes a model to analyze the fault factors of air-to-ground weapon delivery utilizing software fault localization methods. In the previous study, to figure out the factors to affect the accuracy of air-to-ground weapon delivery, the FBEL (Factor-based Error Localization) method had been proposed and the fault factors were analyzed based on the method. But in the study, the correlation between weapon delivery accuracy and the fault factors could not be revealed because the firing accuracy among several factors was fixed. In this paper we propose a more precise fault analysis model driven through a study of the correlation among the fault factors of weapon delivery, and a method to estimate the possibility of faults with the limited number of test cases utilizing the model. The effectiveness of proposed method is verified through the simulation utilizing real delivery data. and weapons delivery testing in the evaluation of which element affecting the accuracy of analysis that was available to be used successfully.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.551-560
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• 2010

In this paper, we suggest a localization method of factors affecting the accuracy of Air-to-Ground weapon delivery. The proposed method, called FBEL(Factor-Based Error Localization), is based on the fault localization technique widely utilized in the realm of software engineering field. FBEL localizes the major factors affecting the performance of weapon delivery. To analyze the effectiveness and the applicability of FBEL, we applied FBEL to real firing data and got the major factors caused the errors. We expect that the method could contribute to improve the quality of weapon delivery system. We also expect that it may aid improvement of pilot capability greatly, if it is applied to pilot firing training.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.806-814
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• 2019

One of the future weapon systems is the individual smart weapon which has a structure mounted on the forearm of soldiers. The structure may cause injuries or affect the accuracy of fire due to its impact on joints when shooting. This paper proposes human-impact interaction modeling and a verification methodology in order to estimate the impact of fire applied to the forearm. For this purpose, a human musculoskeletal model was constructed and the joints' behavior in various shooting positions was simulated. In order to verify the simulation results, an impact testing device substituting the smart weapon was made and the experiment was performed on a real human body. This paper compares the simulation results performed under various impact conditions and the experimental values in terms of accuracy and introduces methods to complement them. The results of the study are expected to be a basis for a reliable human-impact interaction modeling, and smart individual weapon development.

• Convergence Security Journal
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• v.11 no.3
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• pp.11-17
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• 2011

The acquisition of weapons systems test and evaluation in the early stages of the acquisition process as a source of data used for modeling and simulation are being actively encouraged. Thus, in the reliability of weapon systems acquisition can be called the most important part, and M&S to apply for this test reliability and accuracy of the assessment can provide, test time and cost savings, the pre-and post-test predictions and available data can provide. In this study, theoretical study of M&S to acquire weapon systems used for the importance of M&S, acquired the characteristics of the model, utilization for weapon systems acquisition, and weapon systems acquisition review for an effective utilization of M&S tries to find out.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.128-130
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• 2012

One of the hot issues on GNSS might be that China declared to broadcast the signal of the new Global Navigation Satellite System called Beidou-Compass in December 2011. The multi-GNSS systems with the existing GPS and GLONASS consist of more than 100 GNSS satellites and transmit their signals in near future. Many benefits are expected in accuracy, availability, integrity and increasing anti-jam performance. In this presentation, we have mainly investigated the latest issue for multi- GNSS and discussed spectrum analysis as well as the accuracy improvement issue. The use of the modern weapon system based on satellite navigation information was also briefly investigated in warfare.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.673-687
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• 2023

Convolutional neural network-based deep learning technology is the most commonly used in image identification, but it requires large-scale data for training. Therefore, application in specific fields in which data acquisition is limited, such as in the military, may be challenging. In particular, the identification of ground weapon systems is a very important mission, and high identification accuracy is required. Accordingly, various studies have been conducted to achieve high performance using small-scale data. Among them, the ensemble method, which achieves excellent performance through the prediction average of the pre-trained models, is the most representative method; however, it requires considerable time and effort to find the optimal combination of ensemble models. In addition, there is a performance limitation in the prediction results obtained by using an ensemble method. Furthermore, it is difficult to obtain the ensemble effect using models with imbalanced classification accuracies. In this paper, we propose a transfer learning-based feature fusion technique for heterogeneous models that extracts and fuses features of pre-trained heterogeneous models and finally, fine-tunes hyperparameters of the fully connected layer to improve the classification accuracy. The experimental results of this study indicate that it is possible to overcome the limitations of the existing ensemble methods by improving the classification accuracy through feature fusion between heterogeneous models based on transfer learning.