Symplectic Attitude Estimation for Small Satellites

Abstract

In this paper, a novel method for efficient high-accuracy satellite attitude estimation is presented. Symplectic numerical methods are applied to the Extended Kalman Filter (EKF) algorithm to give the SKF, which outperforms the standard EKF in the presence of nonlinearity and low measurement noise in the 1-D case. Building on this result, a six-state SKF is compared to an EKF of the same order for satellite attitude estimation. Simulation of a standard small satellite mission demonstrates orders of magnitude improvement in state accuracy and preservation of constants of motion. This new method shows promise for improved attitude estimation onboard resource-constrained small satellites.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA443061

Entities

People

  • James M. Valpiani
  • Phillip L. Palmer

Organizations

  • University of Surrey

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Algorithms
  • Angular Momentum
  • Covariance
  • Dynamics
  • Equations
  • Filters
  • Integrators
  • Kalman Filters
  • Mathematical Filters
  • Measurement
  • Monte Carlo Method
  • Satellite Orientation
  • Simulations
  • Small Satellites
  • Standards

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Inertial Navigation Systems.

Technology Areas

  • Space
  • Space - Satellites
  • Space - Spacecraft Maneuvers