NASA NTRS · 20230010963
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Lauri K. Newman. Conjunction Assessment NASA Best Practices. https://ntrs.nasa.gov/citations/20230010963
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Phase 1 of the UAS-NAS (Unmanned Aircraft Systems-National Airspace System) project focused on MOPS (Minimum Operational Performance Standards) development for large UAS transitioning through Class D, E, and G airspace. Phase 2 activities are currently focused on extended UAS operations in Class D, E, and G airspace, as well as sensors and architectures that will enable DAA (Detect and Avoid) equipment to be installed on a wider range of UAS. Encounters with non-cooperative intruders in low altitude airspace under 10,000 feet will be explored for UAS with a low Size, Weight, and Power (SWaP) radar. New sensors for detecting non-cooperative intruder aircraft will have a more limited detection range and field of regard; therefore, the analysis of non-cooperative encounter geometries may help in developing the requirements for an onboard low SWaP radar (and electro-optical sensor). The current simulation, led by HSI (Human Systems Integration Division at NASA Ames Research Center) as part of the DAA subproject, will support efforts toward developing a modified DAA Well Clear (DWC) definition that would be more appropriate for UAS equipped with limited surveillance and aircraft performance capabilities compared to the Phase 1 DAA system. The findings will inform Phase 2 display requirements for alternative surveillance use cases.
This presentation will display statistical analysis performed with over 150,000 Conjunction Data Messages (CDMs) received for the Earth Observing System (EOS) Aqua, Aura and Terra satellites within the three year period of March 2015 through February 2018. The analysis performed demonstrates the relationship between the covariance of a secondary object and the amount of tracks it receives, as a function of Time to Closest Approach (TCA). The examination indicates that higher tracking frequencies result in lower uncertainties inclusively from the time the data is screened up until TCA. Further investigation displays the impacts of how additional observations of secondary objects lower their position uncertainties and what period of time prior to TCA convergence of the covariance can be expected depending on how well the objects are tracked. Data points from several recent EOS High Interest Events (HIEs) are used to exemplify this analysis.
The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.