Constrained Target Clustering for Military Targeting Process

  • Jungmok Ma Department of Defense Science, Korea National Defense University
Keywords: Target clustering, Constrained k-means clustering, Targeting

Abstract

Constrained target clustering (CTC) is proposed to support the targeting decision-making in the network centric warfare environment. When area targets are detected by sensors, it is required to decide the points at which a missile or bomb is aimed to achieve operational goals. CTC can determine the optimal numbers and positions of aiming points by transforming the targeting problem into clustering-based optimisation problems. The CTC formulations include objective functions and constraints in consideration of area targets, protected objects, target-level background information, lethal radius, and required damage rate. The numerical example shows how to apply the CTC formulation given a sample data set. In order to compare the effects of different constraints, the demonstration explores from an unconstraint problem to constrained problems by adding constraints. The results show that CTC can effectively decide the aiming points with consideration of both targets and capabilities of friendly weapons, and serve as a targeting decision support system in the network centric warfare environment.

Author Biography

Jungmok Ma, Department of Defense Science, Korea National Defense University
Dr Jungmok Ma received his Masters in Industrial Engineering from Pennsylvania State University in 2006 and PhD in Industrial Engineering from University of Illinois at Urbana-Champaign, in 2015. Presently working as an Assistant Professor in the Department of Defense Science, Korea National Defense University. His research interest include : Data analytics and national defence modelling.
Published
2017-09-19
How to Cite
Ma, J. (2017). Constrained Target Clustering for Military Targeting Process. Defence Science Journal, 67(5), 523-528. https://doi.org/10.14429/dsj.67.10441
Section
Computers & Systems Studies