• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.359-363
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• 2008

In recent warfare, importance of counter-fire is increased. New weapon system and counter-fire have critical impact on defeating of the enemy. At an initial battle counter-fire, we need to study about striking plan against the enemy mine artillery. In this paper, we studied, using MANA(agent based model), how much cannon's hit probability and UAV-based target acquisition have influence on striking the mine artillery. We constructed MANA model based on the characteristics of a regional database of Korean peninsula. If we develop detail database of the ROK Army, the proposed MANA model can be used as a war-game model for the regimental level of the Army.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.143-152
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• 2008

At an initial battle stage, counter-fire capability have critical impact on defeating the enemy in the future warfare. In this paper, we proposed an efficient method of counter-fire execution. To do that, hit-probability for each artillery type was evaluated using CEP and applied to calculate new target reference table of a counter-fire operation. In order to compare new result to the one obtained by using previous reference table from BTCS, we did simulation using MANA model. Simulation outputs show that new method is superior to previous method of counter-fire operation in various scenarios depending upon each method and usage of UAV.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.74-83
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• 2018

It is very crucial activities that Korean army have to detect and recognize enemy's locations and types of weapon of their artillery firstly for effective operation of friendly force's artillery weapons during wartime. For these activities, one of the most critical artillery weapon systems is the anti-artillery radar (hereafter; radars) for immediate counter-fire operations against the target. So, in early wartime these radar's roles are very important for minimizing friendly force's damage because arbiters have to recognize a several enemy's artillery positions quickly and then to take an action right away. Up to date, Republic of Korea Army for tactical artillery operations only depends on individual commander's intuition and capability. Therefore, we propose these radars allocation model based on integer programming that combines ArcGIS (Geographic Information System) analysis data and each radar's performances which include allowable specific ranges of altitude, azimuth (FOV; field of view) and distances for target detection, and weapons types i.e., rocket, mortars and cannon ammo etc. And we demonstrate the effectiveness of their allocation's solution of available various types of radar asset through several experimental scenarios. The proposed model can be ensured the optimal detection coverage, the enhancement of artillery radar's operations and assisting a quick decision for commander finally.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.148-151
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• 2007

The CF(Counter-fire) is neutralizing enemy's all command control systems and fire support elements. It will weaken a battle continuous ability and an intension to fight. At the beginning of the CF is obtaining locations of targets using various detection assets. CF command center processes acquired target information and send it to attacking equipments. The targets are classified into two classes, preplanned target and target of opportunity The target of opportunity is potential threaten, so it needs to take a immediate and exact process for determining location of target of opportunity. This paper proposes the real-time processing algorithm for offensive weapons to strike target of opportunity, and presents the result of its performance.

• Journal of IKEEE
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• v.24 no.4
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• pp.921-930
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• 2020

The Counter-battery radar estimates the origin and impact point of the artillery by tracking the trajectory of the shell. In addition, it has the ability of identifying the type of weapon. Depending on the position between the shell and the radar, the detected signals appear differently. This has ambiguity to distinguish the type of shells. This paper compares fuzzy logic and artificial intelligence, which classifies type of shell using the parameter of signal processing step. According to the research result, artificial intelligence can improve identification rate of type of shell. The data used in the experiment was obtained from a live fire detection test.