@article{ART003204598},
author={Yukyung Shin and Jihyun Roh and Sungbin Ahn and Hyunwoo Jang and Hocheol Jeon},
title={Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={5},
pages={59-68}
TY - JOUR
AU - Yukyung Shin
AU - Jihyun Roh
AU - Sungbin Ahn
AU - Hyunwoo Jang
AU - Hocheol Jeon
TI - Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 5
PB - The Korean Society Of Computer And Information
SP - 59
EP - 68
SN - 1598-849X
AB - This paper proposes an AI-based intent prediction model to enhance the real-time command and control capabilities of the Korea Air and Missile Defense (KAMD) system in response to North Korea's growing ballistic missile and nuclear threats. In previous systems, geographic constraints on the Korean Peninsula and extremely short engagement windows posed significant challenges for real-time response, making it particularly difficult to counter emerging threats such as hypersonic missiles. To overcome these limitations, a rapid prediction system is required that can quickly infer intent based solely on initial trajectory data and support timely interception and follow-on decision-making within limited timeframes.
This study presents an AI model that predicts strategic intent, follow-on actions, and target objectives associated with enemy ballistic missile operations by analyzing trajectory characteristics and operational patterns. The model combines the Vision Transformer (ViT) and Conditional Variational Autoencoder (CVAE), and incorporates both inter-trajectory correlations and temporally accumulated data to enhance adaptability and decision-making accuracy. In particular, the model is trained on a hierarchically structured dataset that reflects real-world target classifications and intent-based operational priorities, enabling more realistic and mission-relevant intent and behavior prediction. This hierarchical approach also reinforces its suitability for real-world defense applications. The proposed model can serve as a core component for real-time situational awareness during operations, as well as for early warning and preemptive threat analysis in peacetime. It demonstrates strong potential for practical integration into defense command systems.
KW - Ballistic Missile Defense;Situational Awareness;Indication Analysis;Defense AI;Vision Transformer (ViT);Conditional Variational Autoencoder (CVAE)
DO -
UR -
ER -
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang and Hocheol Jeon. (2025). Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior. Journal of The Korea Society of Computer and Information, 30(5), 59-68.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang and Hocheol Jeon. 2025, "Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior", Journal of The Korea Society of Computer and Information, vol.30, no.5 pp.59-68.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang, Hocheol Jeon "Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior" Journal of The Korea Society of Computer and Information 30.5 pp.59-68 (2025) : 59.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang, Hocheol Jeon. Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior. 2025; 30(5), 59-68.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang and Hocheol Jeon. "Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior" Journal of The Korea Society of Computer and Information 30, no.5 (2025) : 59-68.
Yukyung Shin; Jihyun Roh; Sungbin Ahn; Hyunwoo Jang; Hocheol Jeon. Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior. Journal of The Korea Society of Computer and Information, 30(5), 59-68.
Yukyung Shin; Jihyun Roh; Sungbin Ahn; Hyunwoo Jang; Hocheol Jeon. Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior. Journal of The Korea Society of Computer and Information. 2025; 30(5) 59-68.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang, Hocheol Jeon. Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior. 2025; 30(5), 59-68.
Yukyung Shin, Jihyun Roh, Sungbin Ahn, Hyunwoo Jang and Hocheol Jeon. "Probabilistic AI-Based Prediction of Missile Target Selection, Launch Intent and Post-Engagement Behavior" Journal of The Korea Society of Computer and Information 30, no.5 (2025) : 59-68.
