McMahon, Jay W. | Search NASA

NASA NTRS2019

Multi-Arc Filtering During the Navigation Campaign of the OSIRIS-REx Mission

The Navigation Campaign of the OSIRIS-REx mission consisted of three phases: Approach, Preliminary Survey and Orbital-A. These phases were designed to optimize the initial characterization of Bennu's mass, shape and spin-state to support a safe orbit insertion and a quick transition to landmark-based optical navigation tracking. The standard orbit determination filtering techniques used to navigate the spacecraft were unable to fit data from these three phases simultaneously due to numerical issues associated with the nonlinear dynamics and the long arc length. Consequently, a multi-arc filtering algorithm was implemented in order to combine the information from each of these arcs. Multi-arc solutions for Bennu's spin state and gravity field are presented here.

French, Andrew S.↗

NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗