Advanced Filtering Techniques Applied to Spaceflight

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX10CE34P
Agency Tracking Number: 095754
Amount: $99,446.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: O4.04
Solicitation Number: N/A
Small Business Information
11560 Forest Lake Drive, Rolla, MO, 65401-7305
DUNS: 175236061
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Jason Searcy
 Principal Investigator
 (502) 655-1952
 jsearcy@istrolla.com
Business Contact
 Sivasubramanya Balakrishnan
Title: Business Official
Phone: (573) 201-1068
Email: bala@istrolla.com
Research Institution
N/A
Abstract
Spacecraft need accurate position and velocity estimates in order to control their orbits. Some missions require more accurate estimates than others, but nearly all missions need some type of orbit determination. IST-Rolla seeks to provide highly accurate algorithms that do not overpower the spacecraft's computer. Many new, powerful algorithms exist such as the particle filter and the unscented Kalman filter, but most of them involve integrating several state vectors, and those integrations devour the computing power available. IST-Rolla will implement the è-D technique, the cost based filter (CBF), and the neural network estimator for orbit determination(developed by IST-Rolla Engineers) and analyze the results. These filters are nonlinear and might provide better accuracy than the extended Kalman filter (EKF) which is widely used, without being computationally cumbersome as the particle filter and unscented Kalman filter. The theta-D technique approximates the solution to the filter-related Ricatti Equation. The CBF is an attempt to formulation of the filter under an 'optimal' framework. The neural network estimator works to estimate the modeling errors online so that the estimates become more accurate.

* Information listed above is at the time of submission. *

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