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Simulating Lucy’s encounters with its target Trojan asteroids

Presentation #104.02 in the session Mission-supporting Practices, Modeling, and Data (Oral Presentation)

Published onOct 23, 2023
Simulating Lucy’s encounters with its target Trojan asteroids

NASA’s Lucy mission will explore 8 Trojan asteroids during a series of 5 encounters over a period of 12 years. Because those encounters are flybys, the windows of opportunity for instrument acquisitions will be short and unique. As such, critical observations must be planned with extreme care in order to ensure that the mission’s science requirements can be met. To help in this task, we have developed the Science Encounter Sequence Simulator (SESS). This powerful tool, based on the NAIF’s SPICE Toolkit and written in Python 3, allows one to simulate the passage of Lucy by each of its targets, while processing a series of commands to adjust the pointing of the instruments and trigger acquisitions. The code outputs attitude data for the spacecraft and the Instrument Pointing Platform (IPP), as well as the position of the scan mirror of the L’Ralph instrument.

SESS models the surface of the asteroid target (using either a simple tri-axial ellipsoid, or a more complex shape provided as a Digital Shape Kernel), allowing estimation of the data resolution and coverage that would result from a given set of observations. Degradation of resolution due to the effects of imperfect pointing stability, jitter, and smear, is taken into account. Using outputs from SESS, we can map the best resolution achieved at each location on the asteroid, as well as produce various other pieces of information for each observation (e.g., phase and incidence angles, local time of day) that allow the Science Team to audit an observation sequence and make recommendations for adjustments and/or request implementation of additional observations.

SESS also allows us to verify the resilience of a sequence of commands against various sources of uncertainty, such as pointing inaccuracies (resulting in degradation of the expected data) or fluctuations in the timing of command execution (potentially leading to collisions between consecutive instructions). Over the last few years, SESS has proven to be an extremely valuable tool to guide the development of Lucy’s activities that maximize the mission’s science return.

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