• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.4
• /
• pp.233-240
• /
• 2022

The smart weapon system is a new weapon system of the future battlefield environment as a miniature guided weapon that performs precision strike missions through terminal phase guidance. However, it has small coverage to guide due to its low maneuverability because the smart weapon is controlled by using actuator of piezoelectric drive type due to the structural limitations. In this paper, we propose a firing data calculation algorithm under non-standard conditions to increase the effectiveness of the smart weapon. The proposed algorithm calculates firing data under non-standard conditions by calibrating firing data under standard conditions using information acquired in battlefield environments. The performance of the proposed algorithm is verified by numerical simulations under various conditions.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.4
• /
• pp.458-466
• /
• 2012

We have developed a weapon effectiveness evaluation model for top-attack smart munitions(WEEM/TASM), which is a many on many Monte Carlo Model evaluating the effectiveness of top-attack smart munitions against armoured ground vehicles. In this model the battle is reduced to a one-sided battle situation in that the target vehicles are regarded as being stationary and passive. It can simulate the whole attack process of smart munitions from firing artillery dispenser to sensing and hitting processes after dispense. It can also calculate the probability of kill of each target and the numbers of rounds required to fulfill the degree of damage in statistical manners. In this paper, we describe the basis for our design concepts reflected in the model to simulate the weapon effectiveness of top-attack smart munitions and provide simulation results for an example case.

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

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.3
• /
• pp.257-265
• /
• 2012

This paper presents a study on characteristics of precession motion of a smart munition. It's a kind of the Sensor Fuzed Weapon. The particular thing for the smart munition is that it has precession motion in the air while the sensor is searching the ground to detect ground vehicles such as tanks. The smart munition has a cylindrical shape and has a sensor attached on its side. Due to its non-uniform mass distribution, its center of gravity(CG) is located away from the center of volume(CV). In order for the smart munition to detect the target effectively, the ground searching pattern of sensor should have an uniform circular form, and for this, the precession motion of smart munition should be in its steady-state. Finally, it is necessary to choose the right initial conditions at the moment of firing, for the steady-state precession motion during flight.

• The Journal of Society for e-Business Studies
• /
• v.10 no.1
• /
• pp.41-60
• /
• 2005

IDEF(Integrated Definition) method, a standard methodology of CALS process modelling, was applied to the weapon system R&D process to provide information modelling by analysing about goal, input, output and constraints in the R&D process. The information to be managed in R&D institutes was identified by using SmartER which is the automation program of IDEF1/1X and obtained information modelling for TO-BE model. The work process of weapon system R&D consists of the concept study phase, the exploration development phase, the system development phase, the prototype manufacturing phase, and the report writing of R&D results phase. The information modelling of weapon system R&D is the R&D work process with information sharing by means of IWSDB Since IDEF is suitable for large scale system development like weapon system R&D, further studies on IDEF would be required to achieve the goal of defense CALS.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.10
• /
• pp.235-243
• /
• 2022

This paper aims to find promising export items for market expansion of defense export items. Germany, the UK, and France were selected as export target countries to obtain unstructured forecast data on weapons system acquisition plans for the next ten years by each country. Using the TF-IDF in text mining analysis, keywords that appeared frequently in data from three countries were derived. As a result of this paper, keywords for each country's major acquisition projects drawing. However, most of the derived keywords were related to mainstay weapon systems produced by domestic defense companies in each country. To discover promising export items from text mining, we proposed that the drawn keywords are distinguished as similar weapon systems. In addition, we assort the weapon systems that the three countries will get a plan to acquire commonly. As a result of this paper, it can be seen that the current promising export item is a weapon system related to the information system. Prioritizing overseas demands using key words can set clear market entry goals. In the case of domestic companies based on needs, it is possible to establish a specific entry strategy. Relevant organizations also can provide customized marketing support.

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

• The Journal of the Korea Contents Association
• /
• v.12 no.11
• /
• pp.502-510
• /
• 2012

As defense science and technology are developing, smart weapons are being developed continually. The collection and analysis of the future strategic weapon information from all over the world have become a greater priority because information sharing became active. So, a system to manage and analyze heterogeneous defense intelligence is required. Semantic Web is the next generation knowledge information management technology for integrating, searching and navigating heterogeneous knowledge resource. Recently, Semantic Web is wildly being used in intelligent information management system. Semantic Web supports the analysis with the high reliability because it supports the simple keyword search as well as the semantic based information retrieval. In this paper, we propose the semantic web based multi-dimensional information analysis system on the national defense weapons that constructs ontology for various weapons information such as weapon specifications, nations, manufacturers and technologies and searches and analyses the specific weapon based on ontology. The proposed system supports the semantic search and multi-dimensional information analysis based on the relations between weapon specifications. Also, our system improves the efficiency on acquiring smart weapon information because it is developed with ontology based on military experts' knowledge and various web documents related with various weapons and intelligent search service.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.1
• /
• pp.39-46
• /
• 2012

An unmanned aerial vehicle (UAV) is a powered aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or non-lethal payload. An UAV is very important weapon system and is currently being employed in many military missions (surveillance, reconnaissance, communication relay, targeting, strike, etc.) in the war. To accomplish UAV's missions, guarantee of survivability should be preceded. The main objective of this study is a local path planning to maximize survivability for UAV on the battlefield of dynamic threats (obstacles, surface-to-air missiles, radar etc.). A local path planning is capable of producing a new path in response to environmental changes. This study suggests a $Smart$ $A^*$ (Smart A-star) algorithm for local path planning. The local path planned by $Smart$ $A^*$ algorithm is compared with the results of existing algorithms ($A^*$ $Replanner$, $D^*$) and evaluated performance of $Smart$ $A^*$ algorithm. The result of suggested algorithm gives the better solutions when compared with existing algorithms.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.11
• /
• pp.9-16
• /
• 2020

The TA-50 aircraft is conducting simulated training on various situations, including air-to-air and air-to-ground fire training, in preparation for air warfare. It is also used for pilot training before actual deployment. However, the TA-50 does not have the ability to operate smart weapon forces, limiting training. Therefore, the purpose of this study is to implement the TA-50 aircraft to enable virtual training of one of the smart weapons, the Point Direct Attack Munition (JDAM). First, JDAM functions implemented in FA-50 aircraft, a model similar to TA-50 aircraft, were analyzed. In addition, since functions implemented in FA-50 aircraft cannot be directly utilized by source code, algorithms were extracted using machine learning techniques(TensorFlow). The implementation of this function is expected to enable realistic training without actually having to be armed. Finally, based on the results of this study, we would like to propose ways to supplement the limitations of the research so that it can be implemented in the same way as it is.