North Korea has repeatedly provoked using unmanned aerial vehicles (UAVs), and the threat posed by UAVs continues to escalate, as evidenced by recent directives involving the use of waste-laden balloons and the development of suicide drones. North Korea’s small UAVs are difficult to detect due to their low radar cross-section (RCS) values, necessitating the efficient deployment and operation of assets for effective response. Against this backdrop, this study aims to predict the infiltration routes of enemy UAVs by considering their perspective, avoiding key facilities and obstacles, and propose deployment strategies to enable rapid detection and response during provocations. Utilizing the Markov Decision Process (MDP) based on previous studies, this research presents a model that reflects both UAV flight characteristics and regional environments. Unlike previous models that designate a single starting point, this study addresses the practical challenge of uncertainty in initial infiltration points by incorporating multiple starting points into the scenarios. By aggregating and integrating the probability maps derived from these variations into a unified map, the model predicts areas with a high likelihood of UAV infiltration over time. Furthermore, based on case studies in the capital region, this research proposes deployment strategies tailored to the specifications of currently known anti-drone integrated systems. These strategies are expected to support military decision-making by enabling the efficient operation of assets in areas with a high probability of UAV infiltration.

Abstract
1. 서 론
2. 문제정의 및 모형 구축
    2.1 문제정의
    2.2 MDP 모형 구성
    2.3. MDP 모형의 실행
3. 모형 실행 결과 및 분석
    3.1. 다수 시작점 적용 모형 실행 결과
    3.2. 가중합을 이용한 결과통합
    3.3. 결과 분석 및 작전 운영 방안
4. 결 론
Reference

• Young-Rong Lim(The Department of Defense Management, Korea National Defense University) | 임영롱 (국방대학교 국방관리대학원)
• Moon-Gul Lee(The Department of Defense Management, Korea National Defense University) | 이문걸 (국방대학교 국방관리대학원) Corresponding author