Developing a Certifiable UAS reliability Assessment Approach Through Algorithmic Redundancy

Manned aircraft, civilian or military, are required to meet certain reliability standards specified by the FAA in order to operate in the US national airspace. These reliability standards are typically met via hardware redundancy. Multiple, dissimilar components of hardware designated for a single purpose increases the physical redundancy and offers a viable way to detect and correct for hardware malfunctions. Unmanned Aircraft Systems (UAS) are often subject to weight/power constraints and therefore unable to accommodate similar redundancies. A common approach to solving this problem has been to employ analytical redundancy in the form of fault detection and isolation (FDI) algorithms. Although significant breakthroughs have been achieved in increasing UAS redundancies analytically, certification has been challenging. The primary objective of the proposed work is to develop a software architecture for UAS that provides certifiable analytical redundancy. The proposed approach is called algorithmic redundancy, owing to its underlying philosophy of increasing UAS reliability via multiple, dissimilar FDI algorithms. Certification of an algorithmically redundant system relies on well-established methods similar to those for hardware redundant systems. We propose to develop a framework for evaluating and selecting FDI algorithms, combining them to build algorithmically redundant software and finally, assess the overall reliability for certification

The proposed algorithmic redundancy framework for UAS directly addresses three of the six strategic thrusts in the current NASA ARMD Strategic Implementation Plan. Thrust 1: �Safe, Efficient Growth in Global Operations� will be addressed by a sustained focus on reducing risks in UAS to maintain acceptable levels of safety for all air traffic. Thrust 5: �Real-time, System-Wide Safety Assurance� will be addressed by the development of an analytic technique that directly addresses and mitigates UAS risks toward integrated, system-wide safety assurance. Thrust 6: �Assured Autonomy for Aviation Transformation� is addressed by the development of an innovative redundant FDI framework that will better enable safe integration of UAS into the NAS. NASA is also addressing air traffic management for low-altitude drones with the goal of developing a system to ensure safe entry of new UAS. The proposed algorithmic redundancy framework will benefit this system by providing safety assurance.

The low-altitude (<500 ft.) drone industry is growing rapidly in the commercial sector with the emergence of new autonomous UAS applications including package delivery, infrastructure inspection, and environmental and agricultural monitoring. At higher altitudes, emerging commercial UAS technologies include high-altitude communications relay systems for expanding internet access to remote areas. The proposed algorithmic redundancy framework will be beneficial for ensuring that new commercial UAS in these applications will be safely integrated with less hardware redundancy, reducing weight and increasing achievable performance bounds. UAS are prolific in the DoD with many currently operational UAS and others that are nearing operational status. There are several other DoD programs where smaller UAS are at lower but increasing TRLs. The proposed algorithmic redundancy framework has direct application to these DoD UAS by providing detailed risk assessment and mitigation for safety assurance using less hardware redundancy, resulting in lower weight and increased performance.

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