DAAMSIM: A simulation framework for establishing detect and avoid SYSTEM requirements

Abstract

Performance requirements for detect, alert, and avoid (DAA) systems for remotely piloted aircraft systems (RPAS) are under development by many regulatory agencies and standards bodies. A DAA system can be decomposed into three functions, “detect” — situational awareness; “alert” — determination of traffic that may be in conflict, evaluation of the de-conflicting flight path, and informing the pilot-in-command; and “avoid” — avoidance maneuver execution, and determination of “clear of conflict”. The “Detect” function of a DAA system depends on the sensor, target, and environment characteristics (e.g., signal-to-noise ratio of the target vs. background). The “alert” function depends on conflict prediction algorithms and human factors requirements. The “avoid” function depends on the RPAS maneuvering performance, airspace “rules”, and the size of the protection volume. The aforementioned factors impact the time required to calculate, and execute, an avoidance maneuver that will guarantee a prescribed miss distance, and dominate the “detect” requirements of a sensor. This paper describes DAAMSim: a publicly available modeling and simulation framework, developed by the National Research Council of Canada, to support the determination of DAA system requirements, and evaluation of DAA system performance. The framework described herein incorporates the functional components including various sensor, tracker, and avoid models; data replay; visualization tools; and offline metrics. Further, this paper presents sample results of the framework’s ability to determine DAA system requirements for various degrees of RPAS and intruder performance, and concludes with a description of future work activities.

Keywords

• risk ratio
• detect and avoid
• modelling and simulation
• RPAS
• UAS
• ratio de risque