Research report | An Evidential Network Approach Applied to Threat Evaluation in Above Water Warfare
Threat prioritisation is a critical step in the detect-to-engage sequence during naval combat. As the warfighter's task requires the analysis of ever more complex scenarios, the ability to analyse all situational awareness information in a limited timeframe becomes more difficult, and the requirement for real-time tactical decision aids gains more prominence. The Evidential Network Technique is reviewed in this report with example analyses. In addition, a prototype threat evaluation model is presented for specific use in the above water warfare domain.
Threat evaluation and prioritisation in the above water warfare (AWW) domain is a critical component of the Detect-to-Engage Sequence, and is typically undertaken by a Principle Warfare Officer or person(s) of equivalent training. In modern fire control systems, threat prioritisation can be performed in manual or automatic modes, or some combination thereof, at the discretion of warfare officers who oversee combat operations. Such decisions depend largely on the number and type of potential threats and the time available for tactical decision making. With potentially multiple targets and constantly updating situational awareness data from multiple sensors, the demands on combat system operators to prioritise threats in a timely manner can be severely tested. In such cases, the requirement for tactical decision aids gains more prominence.
A decision aid designed to facilitate prioritisation of threats would provide viable, rapid real-time response options for the warfighter to consider in parallel to his/her own threat prioritisation proposals.
This report is a review of the application of an Evidential Network, with the objective to develop a tactical decision aid for use in real-time AWW.
A MATLAB® algorithm produced by Benavoli et al. , which had only previously been utilised for threat evaluation in the air domain, was applied in this study to the AWW problem. However, the software requires further development to streamline its use, including the development of a Graphical User Interface (GUI).
The Evidential Network approach is more likely to provide realistic threat prioritisation results due to its capability for modelling uncertainty and ignorance in situational awareness. A notable downside is that this approach is significantly more mathematically complex.
The threat prioritisation study undertaken in this report goes hand-in-hand with a related previous study undertaken by the author in weapon target assignment . The application of Evidential Network theory for Threat Evaluation, and further development of the related MATLAB algorithms, can be combined with the previous study, to automate the Threat Evaluation and Weapon Assignment process.