Accession Number:

AD1092247

Title:

Attitude Mode Estimation from Computer Vision Data via Multiple Model Methods

Descriptive Note:

Technical Report,22 Dec 2017,18 Dec 2019

Corporate Author:

The Research Fundation for SUNY University of Buffalo Amherst United States

Personal Author(s):

Report Date:

2019-12-18

Pagination or Media Count:

30.0

Abstract:

This report outlines the finished result in the scope of the work, which is Pointing Mode Determination of Resident Space Objects RSOs. RSOs are any object orbiting another body, but this work focuses on selective satellites of which little information is known. The goal is to improve Space Situational Awareness SSA to be able to determine the intent of the spacecraft, as well as provide any other useful information. This information can be gathered using algorithms with information from resolved images of the RSO. The resolved images can be obtained with an Observing Satellite OS, which is tasked with staying close to and pointing its sensor in the direction of the RSO. For the purposes of this work, the OS is already in place, orbiting near the RSO with a controller keeping the OS pointing at the RSO, and is taking resolved images. The input to the provided work is in the form of already-extracted feature points of the RSO in a two-dimensional image plane, used as measurements for the attitude determination algorithms of the Extended Kalman Filter.

Subject Categories:

  • Unmanned Spacecraft

Distribution Statement:

APPROVED FOR PUBLIC RELEASE