Evaluation of Counter Unmanned Aerial Systems through the levels

Countering unmanned aerial threats is critical for both military and civilian surveillance and protection systems. The complementarity and redundancy of sensors enables detecting, tracking and classifying Unmanned Aerial Vehicles (UAVs), further assessing their possible threat and planning the proper counter-measure. Despite efforts to develop dedicated systems (sensors, processing, hard and soft kill systems), Counter Unmanned Aerial Systems (CUAS) are often deployed in complex civilian areas, which requires an adequate understanding of the situation including the UAVs behavior for an appropriate response. The evaluation of a CUAS should thus consider not only its ability to provide a tactical picture of sufficient quality, but also its ability to provide semantic information, to establish possible links between objects and to contextualize their behavior. In this paper, we set up the basics for an evaluation platform covering the lower levels but also higher levels of the JDL (Joint Directors of Laboratories) functional model of information fusion. We consider the six classical criteria of a tactical picture (used in Level 1) and extend them to higher level tasks. Evaluation criteria are aligned with the URREF (Uncertainty Representation and Reasoning Evaluation Framework) ontology evaluation criteria. Furthermore, we propose some metrics to quantity such evaluation criteria. The framework is illustrated in a CUAS scenario, with data provided by the LEXLUTOR platform. Several fusion solutions are compared which differ in the way uncertainty is represented, handled and provided to the user.