INTELLIGENT OBSERVING UNCOOPERATIVE SPACE OBJECTS

Abstract

Non-cooperative space objects include malfunctioning satellites and space debris which is increasing. Characterizing a non-cooperative space object is a crucial step for a chaser observation satellite to determine proximity to other satellites conducting surveillance, space debris removal, and on-orbit satellite repairing. Different from rendezvous and docking with cooperative objects such as the International Space Station, the chaser satellite lacks reliable information about the non-cooperative object. The goal of this project is to develop theoretical and computational methodologies that enable intelligent decisions from cooperative satellites on how to observe non-cooperative space objects. We propose a dynamic data driven applications systems (DDDAS)-based framework under which the object model (e.g., predictive kinematics, physical characterization, mission behavior) is refined incrementally using the sensor measurements from chaser spacecraft, while concurrently optimizing collect measurements (including both translations and rotations) to enhance the posterior belief about the object model. In contrast to existing studies which treat object motion predictions, chaser approach path generation, and measurement collections separately, this proposal considers these issues in a coupled way. By developing a holistic approach to space object tracking will lead to significant performance improvements over current methods. Theories and algorithms under development of this research are fundamental in nature but have the potential to transition for testing through demonstrations at US Space Force facilities with representative data. The project will open the door to an innovative approach that optimally and autonomously collect measurement data within a congestive and contentious space environment.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 20, 2023
Source ID
FA95502210364

Entities

People

  • Xiaoli Bai

Organizations

  • Air Force Office of Scientific Research
  • Rutgers University
  • United States Air Force

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Sensor Fusion and Tracking Systems.
  • Space Exploration and Orbital Mechanics.

Technology Areas

  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers