The ability for small Unmanned Aircraft Systems (sUAS) to safely operate beyond line of sight is of great interest to consumers, businesses, and scientific research. In this work, we investigate Sense and Avoid (SAA) algorithms for sUAS encounters using three 4k cameras for separation distances between 200m and 2000m. Video is recorded of different sUAS platforms designed to appear similar to expected air traffic, under varying weather conditions and flight encounter scenarios. University partners and NASA both developed SAA methods presented in this report. This report is organized as follows: Introduction, Experimental Design, Description of video and GPS data, NASA Methods and Results, University Partner Results, Recommendations, and Conclusions.

The goal of the National Aeronautics and Space Administration's (NASA) Aviation Safety program is to reduce the number of fatal aircraft accidents worldwide by 80% within 10 years and by 90% within 20 years. Because flight crew error is cited as a causal factor in approximately 70% of aviation accidents occurring from 1985 to 1995 (Boeing, 1996), NASA Langley Research Center (LaRC) is leading studies for the Aviation Safety program toward reducing flight crew error with synthetic vision and improved aviation weather information. Synthetic vision is defined as augmented visual displays in which terrain, traffic, and obstacle database information, enhanced by computer graphics and other information, are presented to the flight crew. The Aviation Weather Information (AWIN) project involves determining flight crew requirements for cockpit weather information, integrating weather information products on the flight deck, and designing proper interfaces for their use. This paper presents results of studies to date in these two areas which are leading to new design concepts for significant mitigation of flight crew error. Indications arc presented of the relative contributions of these teclmologies to the Aviation Safety program goal of reduced aviation accidents worldwide.