NASA SBIR 2019-I Solicitation

Proposal Summary


PROPOSAL NUMBER:
 19-1- H9.03-3622
SUBTOPIC TITLE:
 Flight Dynamics and Navigation Technology
PROPOSAL TITLE:
 Efficient Realistic Conjunction Analysis (EReCA)
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Stellar Science Ltd Co
6565 Americas Parkway Northeast, Suite 925
Albuquerque, NM 87110- 8123
(877) 763-8268

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Dr. Irene Budianto-Ho
E-mail:
irene@stellarscience.com
Address:
6565 Americas Parkway NE Suite 925 Albuquerque, NM 87110 - 8123
Phone:
(877) 763-8268

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
David Myers
E-mail:
djm@stellarscience.com
Address:
6565 Americas Parkway NE Suite 925 Albuquerque, NM 87110 - 8123
Phone:
(505) 417-1919
Estimated Technology Readiness Level (TRL) :
Begin: 3
End: 5
Technical Abstract (Limit 2000 characters, approximately 200 words)

The number of artificial objects orbiting the Earth today creates a challenging environment for the protection and safe operation of satellites. With the rise of micro-satellites, nano-satellites, and communications and sensing constellations consisting of hundreds of satellites, the space population is certain to multiply at a robust pace during the next decades of spaceflight, further exacerbating the threat of on-orbit collision posed to active satellites. Soon, the safety of our space assets will require highly accurate and efficient collision prediction.

The keys to a collision prediction system that can handle the future growth of data are accuracy in data representation, efficient screening techniques, and automation. Accurate collision risk assessment requires a realistic representation of orbit uncertainty in the calculation. However, accuracy must not come with high computational cost. Smart hardware choices, parallelization, and efficient screening technique are essential to utilize non-Gaussian representation of orbit uncertainties with its computationally-intensive tasks. Automation of the analysis will further improve overall efficiency so that the conjunction assessment process can begin as soon as a warning is received. Stellar Science proposes a novel solution to improve the accuracy and dramatically increase the systematic efficiency of collision probability assessment for objects in Earth orbit. Our proposed system, Efficient and Realistic Conjunction Analysis (EReCA), will leverage recent advances in non-Gaussian orbital uncertainty propagation and existing Monte Carlo techniques for reliable conjunction assessment, as well as current and past work by Stellar Science on the use of spatial data structures to quickly process a large set of data. Our system will be built on a service-oriented approach and will introduce end-to-end automation of the conjunction analysis process to improve efficiency.
 

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

NASA’s stake in avoiding space collisions is particularly high given the level of visibility of their programs, the value of their assets, and their commitment to orbital debris mitigation. NASA established CARA for the protection and safe operation of its robotic missions. Other U.S. government agencies have also come to rely on CARA for risk assessments of potential collision with their satellites. The technology presented in this proposal directly addresses the problem of efficient and accurate conjunction assessment facing the CARA team.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

There is no shortage of organizations with a keen interest in avoiding satellite collisions in a $383.5 billion global space economy. Most of these rely on CSpOC notifications for collision alerts. However, each satellite operator must manage its own risks. The commercial monitoring service AGI’s ComSpOC® also would invest in an efficient and accurate collision prediction system, such as EReCA.

Duration: 6

Form Generated on 06/16/2019 23:21:49