This paper presents an Orbit Maintenance Module (OMM) for Tradespace Analysis Tool for Constellations (TAT-C), a software package to explore a wide range of tradespaces to design constellations for Earth observation. As the tool is primarily meant for rapid pre-Phase A analysis, it has to be able to estimate trade-offs and overall performance parameters with simplified models on a personal computer in a reasonable time frame. The OMM estimates the secular drift of relative orbital elements between pairs of satellites due to the gravitational `J2' effects and the drift of altitude due to the atmospheric drag, and computes maneuvers to correct them. The J2 is a predominant term in the gravitational zonal harmonics which, primarily, affects the argument of perigee and the mean anomaly. We estimate the drift of these elements between pairs of satellites using a fourth-order polynomial, which is trained using machine learning and which depends on the inclination, altitude and initial angular separation in true anomaly and right ascension of the ascending node. An analytical model is used to predict the deorbiting rate depending on the initial altitude, the solar cycle, the satellite's mass, drag coefficient and area. In order to maintain the required topology of a constellation, the drift of orbital elements is compensated using emulated orbital maneuvers, when satellites breach a user-defined threshold percentage of their nominal values. We assume simple orbital maneuvers (i.e., orbit phasing and Hohmann transfer) to determine the required delta-V, propellant consumption and frequency of maneuvers. These parameters are provided as outputs of the TAT-C's OMM, which advises the user on trade-offs between performance and maintenance overhead of all enumerated constellation architectures. The maneuver metrics can be used to determine various dependent metrics, such as time available for observations, impact on total satellite mass, and mission cost.
|Title of host publication||IEEE Aerospace Conference Proceedings|
|Publication status||Published - 2019|
|MoE publication type||A4 Article in a conference publication|
|Event||IEEE Aerospace Conference - Big Sky, United States|
Duration: 2 Mar 2019 → 9 Mar 2019
|Conference||IEEE Aerospace Conference|
|Period||02/03/2019 → 09/03/2019|