Assuring Cognitive EW Systems

This presentation describes some of the challenges associated with testing the performance of Cognitive Electronic Warfare (CogEW) systems. CogEW incorporates Artificial Intelligence (AI) enables EW systems to respond more quickly and effectively to real-world conditions with complex and novel emitters; these systems learn post-deployment from novel experiences in the field. Cognitive capabilities will force multiple paradigm shifts from legacy test and evaluation (T&E) approaches. Notably, the system may never be the same twice. These paradigm shifts highlight changes needed in T&E processes, infrastructure, and requirements to support this capability. T&E processes must validate the learning process, rather than validating the learned model. Testing must become a continuous process, rather than a final exam. T&E infrastructure must adopt a mixed-resolution closed-loop T&E framework, and a data fabric that supports rapid test analysis. Finally, requirements should be placed on cognitive systems for data collection, transparency, and rules for how to interact with legacy systems.

Speaker and Presenter Information

Dr. Karen Haigh (https://sites.google.com/site/kzhaigh) is an expert and consultant in Cognitive EW and embedded AI. Her focus is on physical systems with limited communications and limited computation resources that must perform under fast hard-real-time requirements. She co-authored the book "Cognitive Electronic Warfare: An Artificial Intelligence Approach" [Artech 2021]. She received her PhD in from Carnegie Mellon University in Computer Science with a focus on AI and Robotics. She is a Fellow of the IEEE for contributions to closed-loop control of embedded systems, and a Fellow of AAIA for outstanding achievements in the area of smart homes.