The PUNCH Mission Planning System; the Next Iteration in Micro-Satellite Constellation Operations

The Polarimeter to UNify the Corona and Heliosphere (PUNCH) is a NASA Small Explorer (SMEX) mission that will be operated by the Southwest Research Institute (SwRI) with the goal to determine the cross-scale processes that unify the solar corona and heliosphere. To accomplish this mission PUNCH makes global, deep-field, 3D observations of the young solar wind from the solar corona to the inner heliosphere, closing a 50-year gap in measurement and understanding. A constellation of four small satellites in Sun-synchronous low Earth orbit produces deep field, continuous, 3D images of the corona and young solar wind from 6 solar radii to 180 solar radii in polarized visible light. Each spacecraft carries one instrument. On one spacecraft a Narrow Field Imager (NFI) captures the entire outer corona from 6 to 32 solar radii. On the other three spacecraft, Wide Field Imagers (WFIs) capture from 20 to 180 solar radii. A common imager detector allows images from all four Observatories to be combined into higher-order science data products. In this paper, we discuss how the experience SwRI gained by operating the NASA CYclone Global Navigation Satellite System (CYGNSS) influenced the design of the Mission Planning System (MPS) for PUNCH. The PUNCH mission planning system shares the same high-level architecture as CYGNSS, in so much as it is a task-based planning system that utilizes ASCII text files for inputs and utilizes Systems Tool Kit (STK) Scheduler for task deconfliction. While PUNCH's MPS inherits much of its code from CYGNSS's MPS, there was much refactoring done. Unnecessary and duplicate code was also eliminated, and the database was simplified. Some of these decisions were a result of the lessons learned from the Trojan Planning File Generator (TPFG); the Science Planning system developed by SwRI for the NASA Lucy mission. We also discuss the reasons for these design decisions, some of which are efficiency improvements derived from the experience SwRI gained from operating several missions, others are driven by the nature of the science collected between different missions. Finally, we discuss how we incorporated unit testing of the software from the beginning of the project.