Desensitized Optimal Filtering and Sensor Fusion Tool Kit

Award Information
Agency:
National Aeronautics and Space Administration
Amount:
$599,860.00
Program:
SBIR
Contract:
NNX11CA58C
Solitcitation Year:
2009
Solicitation Number:
N/A
Branch:
N/A
Award Year:
2011
Phase:
Phase II
Agency Tracking Number:
094535
Solicitation Topic Code:
O4.04
Small Business Information
Analytical Mechanics Associates, Inc.
VA, Hampton, VA, 23666-1568
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
045856622
Principal Investigator
 Christopher Karlgaard
 Principal Investigator
 (757) 865-0000
 karlgaard@ama-inc.com
Business Contact
 Anu Bedi
Title: Business Official
Phone: (757) 757-0000
Email: anub@ama-inc.com
Research Institution
 Stub
Abstract
Research on desensitized optimal filtering techniques and a navigation and sensor fusion tool kit using advanced filtering techniques is proposed. Research focuses on reducing the sensitivity of Kalman filters with respect to model parameter uncertainties using a robust trajectory optimization approach called Desensitized Optimal Control, developed by the proposing company. The proposed tool kit implements the research results as well as recent advances in robust and/or adaptive generalized Kalman and Sigma-Point filters for non-Gaussian problems with uncertain error statistics.The proposed research and development brings new filtering and sensor fusion techniques to NASA and industry in a convenient package which can be used as a stand-alone toolbox, either for ground support or for onboard applications. Its modular structure enables it to be readily integrated with other tools, and thus enhances the existing fleet of applications.The desensitized optimal filtering research and the feasibility study on components of the proposed tool kit will be carried out concurrently. The tool kit is a generic stand-alone application, and has a modularized structure which facilitates easy integration with existing tools. A suite of sensor models and noise distributions as well as Monte-Carlo analysis capability are included to enable statistical performance evaluations.

* information listed above is at the time of submission.

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