# A Novel Two-Staged Decision Support Based Threat Evaluation And Weapon Assignment Algorithm Asset-Based Dynamic Weapon Scheduling Using Artificial Intelligence Techinques

Huma Naeem, Asif Masood, Mukhtar Hussain, Shoab A. Khan Department of Computer Science, National University of Science and Technology, Rawalpindi, Pakistan jinnny@gmail.com , amasood@mcs.edu.pk, mukhtar.dr@gmail.com, kshoab@yahoo.com Abstract**—. Surveillance control and reporting (SCR) system for** air threats play an important role in the defense of a country. SCR system corresponds to air and ground situation management/processing along with information fusion, communication, coordination, simulation and other critical defense oriented tasks. Threat Evaluation and Weapon Assignment (TEWA) sits at the core of SCR system. In such a system, maximal or near maximal utilization of constrained resources is of extreme importance. Manual TEWA systems cannot provide optimality because of different limitations e.g. surface to air missile (SAM) can fire from a distance of 5Km, but manual TEWA systems are constrained by human vision range and other constraints. Current TEWA systems usually work on target-by-target basis using some type of greedy algorithm thus affecting the optimality of the solution and failing in multi-target scenario. his paper relates to a novel two-staged flexible dynamic decision support based optimal threat evaluation and weapon assignment algorithm for multi-target air-borne threats. 

Keywords- Optimization Algorithm; Threat Evaluation (TE) 
and Weapon Assignment (WA) Algorithm (TEWA); Decision Support System (DSS); Stable Marriage Algorithm (SMA); Cybernetics Application, preferential and subtractive defense strategies. 

## I. Introduction

Defense of a country is of supreme importance in this technology saturated age. Automated and semi-automated defense oriented tools can be seen as a military response to this technology pressure. Digitized surveillance control and reporting (SCR) system for air threats is one such system. SCR system corresponds to air and ground situation management/processing along with information fusion, communication, coordination, simulation and other critical defense oriented tasks. Threat Evaluation and Weapon Assignment (TEWA) sits at the core of SCR system. Figure 1 shows graphical representation of integrated digitized surveillance process. 

TEWA is a complex system that maintains an ongoing interaction with a non-deterministic and dynamic environment. It includes continuous intelligent threat detection, identification and evaluation coupled with resource allocation in real time and in response to a variety of events taking place in the environment. The situation is more complex when there are multiple potential threats. TEWA can be divided into two subprocesses i.e. threat Evaluation (TW) and Weapon Assignment 
(WA). A closed loop TEWA process is not only NP-Complete but also, discrete, dynamic, non-linear, stochastic, and large 

![0_image_0.png](0_image_0.png)

scale in terms of increased number of WS and targets [3], it is difficult to solve it optimally when number of threats and weapons is large, as computation time of the solution increases rapidly with the size of problem. For an efficient TEWA 
system there is a need to create a balance between usefulness and effectiveness of weapon systems (WSs) [2], [3]. 

Manual TEWA systems cannot provide optimality because of little amount of information available and established situational picture (limited awareness and information), 
operator's limitations like vision range constraint, experience, observation, understanding of the situation and mental condition. This is a known fact that humans are prone to errors especially in stressful conditions. As a consequence in military domain, when facing a real attack scenario, an operator may fail to come up with an optimal strategy to neutralize targets. This may cause a lot of ammunition loss with an increased probability of expensive asset damage. Moreover, most semiautomated TEWA systems usually work on target-by-target basis using some type of greedy algorithm thus affecting the optimality of the solution and failing in multi-target scenario [4]. Figure 2 shows graphical representation of TEWA along with two critical concerns found in multi-target scenarios. 

This paper relates to the design, simulation and analysis of a novel two-staged flexible dynamic decision support based 