Advanced Estimation and Data Fusion Strategies for Space Surveillance/Reconnaissance

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9451-10-M-0089
Agency Tracking Number: F093-012-0746
Amount: $99,969.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: AF093-012
Solicitation Number: 2009.3
Small Business Information
1300 N. Holopono St, Suite 116, Kihei, HI, 96753
DUNS: 784201746
HUBZone Owned: Y
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Keric Hill
 Principal Investigator
 (808) 264-9813
Business Contact
 Don Forrester
Title: CFO
Phone: (808) 268-4478
Research Institution
The accurate tracking of resident space objects (RSO)s depends on the rapid estimation of orbits using the knowledge gained from sparsely sampled observations of satellites under the influence of interacting gravitational and drag effects. Examples of scenarios operating within this environment include tasking follow up observations of debris created from collision events, accurately establishing the identity of objects that are located within close proximity, and reacting to controlled on-orbit deployments of additional space objects. New near real time and computationally efficient algorithms that can estimate non-Gaussian RSO error characteristics are available that could characterize RSO error to a much higher fidelity than current methods. For example, it has been shown that typical “banana-shaped” covariance profiles displaying more uncertainty along-track, than cross-track are reproducible with this technique. This type of information combined with orbital estimates provides more actionable space situational awareness (SSA) knowledge. Combined with an innovative space surveillance network (SSN) simulator that uses smart scheduling of assets in a flexible and responsive publish-and-subscribe network environment, these algorithms will be developed and tested for their applicability to improving the speed, accuracy and responsiveness of RSO tracking. BENEFIT: Currently, the SSN uses the NORAD SGP4 orbit models for predicting satellite positions that do not have the associated covariance estimates. PDS will provide a performance assessment of utilizing these innovative orbit estimation and RSO track association algorithms developed under this project by testing their accuracy and responsiveness of RSO tracking against realistic use cases generated with an innovative space surveillance network (SSN) simulator. Once these algorithms are validated under “real world” simulations, PDS will test and validate these algorithms with actual SSN data. PDS intends to work closely with the Air Force in transferring technology for their critical objectives. The primary DoD end-customer for these algorithms is the JFCC-Space through the Joint Space Operations Center (JSpOC), which detects, tracks, and identifies all man-made objects in Earth orbit. Through current program experiences, PDS understands the acquisition process involved in transitioning algorithms from concept to validation, development, testing, (SMC SSA Technology Branch) and deliverance of an operational product to the warfighter (AF Space Command).

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

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