Multi-target Threat Assessment Method Based on An Effective Reduction Method

Abstract

Multi-target threat assessment is an important prerequisite for jamming resource allocation and operational preparations. The more accurate the threat assessment is, the better the effect of decision support will be. In the face of complex battlefield environment and massive data, enough threat assessment attributes are conducive to improving the accuracy and credibility of the threat assessment. However, it also generates a huge amount of computation, which may cause huge challenge for both hardware and software to get the required results in a limited time. Thus, an effective attribute reduction method is proposed. Firstly, enough evaluation attributes are selected for specific threat targets. The attributes are reduced by analytic network process (AHP), the minimum variance method is used to optimize the attribute data, and then the rough set theory is applied to further optimize the threat evaluation attributes. Finally, the rationality and effectiveness are illustrated by an example of air target threat assessment