NASA NTRS · 20170007067
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Tarzi, Zahi, Berry, David, Roncoli, Ralph. 2015-10-19. An Updated Process for Automated Deepspace Conjunction Assessment. https://ntrs.nasa.gov/citations/20170007067
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There is currently a high level of interest in the areas of conjunction assessment and collision avoidance from organizations conducting space operations. Current conjunction assessment activity is mainly focused on spacecraft and debris in the Earth orbital environment [1]. However, collisions are possible in other orbital environments as well [2]. This paper will focus on the current operations of and recent updates to the Multimission Automated Deep Space Conjunction Assessment Process (MADCAP) used at the Jet Propulsion Laboratory for NASA to perform conjunction assessment at Mars and the Moon. Various space agencies have satellites in orbit at Mars and the Moon with additional future missions planned. The consequences of collisions are catastrophically high. Intuitive notions predict low probability of collisions in these sparsely populated environments, but may be inaccurate due to several factors. Orbits of scientific interest often tend to have similar characteristics as do the orbits of spacecraft that provide a communications relay for surface missions. The MADCAP process is controlled by an automated scheduler which initializes analysis based on a set timetable or the appearance of new ephemeris files either locally or on the Deep Space Network (DSN) Portal. The process then generates and communicates reports which are used to facilitate collision avoidance decisions. The paper also describes the operational experience and utilization of the automated tool during periods of high activity and interest such as: the close approaches of NASA's Lunar Atmosphere & Dust Environment Explorer (LADEE) and Lunar Reconnaissance Orbiter (LRO) during the LADEE mission. In addition, special consideration was required for the treatment of missions with rapidly varying orbits and less reliable long term downtrack estimates; in particular this was necessitated by perturbations to MAVEN's orbit induced by the Martian atmosphere. The application of special techniques to non-operational spacecraft with large uncertainties is also studied. Areas for future work are also described. Although the applications discussed in this paper are in the Martian and Lunar environments, the techniques are not unique to these bodies and could be applied to other orbital environments.
Aircraft not receiving radar services rely on see and avoid and radio coordination via Common Traffic Advisory Frequencies to remain well clear of each other and avoid mid-air collisions. Radio coordination is usually performed in the vicinity of non-towered airports whereas non-radar services en-route operations rely solely on see and avoid. This paper presents the results of a simulation study of the effectiveness of assistive detect and avoid technologies when used to enhance pilots’ ability to see and avoid nearby traffic. Three different experimental conditions are modeled, representing “unaided see and avoid”, “see and avoid with traffic advisories”, and “see and avoid with assistive detect and avoid technology”. The effectiveness of see and avoid is evaluated using a set of head-on, crossing, and overtaking encounter scenarios and a model of visual acquisition embedded in a Monte Carlo simulation. The effectiveness of assistive detect and avoid is estimated for the same encounter scenarios. A prototype system for detect and avoid and a summary of results are presented. Preliminary results strongly suggest that assistive detect and avoid could greatly enhance the capabilities of flight crews to avoid traffic and remain well clear.