ADVANCED SPACE LLC — National Aeronautics and Space Administration SBIR Phase I: H9

ADVANCED SPACE LLC — SBIR Phase I award from National Aeronautics and Space Administration.

Amount
$124,975
Agency
National Aeronautics and Space Administration
Program / Phase
SBIR · Phase I
Topic
H9
Solicitation
SBIR_19_P1
NAICS
Place of performance
CO
Period
2019-08-19 → 2020-02-18

Description

Traditionally, limitations in spacecraft computing capabilities have limited the amount of collected data that is stored onboard a spacecraft. The lack of sufficient onboard resources have also resulted in custom data storage architectures that vary by mission in the absence of a standard data access framework. Onboard computing capabilities have improved significantly through targeted investments in technologies in recent years and will continue to grow in the future. Additionally, ground-based processing, nbsp;which inherits time-lag, communication availability, and limited bandwidth issues, will be incapable of meeting the increasing demands for operational and scientific data processing objectives. As flight software systems mature to take advantage of increased onboard computing resources, a standardized infrastructure will be needed to store and access data onboard. Advanced Space proposes to demonstrate the feasibility of ODIS, the Onboard Data Infrastructure for Spacecraft. ODIS utilizes standard SQL interfaces and open-source relational databases that operate within a standardized framework for data storage and retrieval. Additionally, Advanced Space proposes to design and implement a Database Memory Manager (DMM) that will allow increased data storage onboard a spacecraft. ODIS will be demonstrated within NASArsquo;s Core Flight System (cFS) software architecture. With the ability to utilize standard industry-accepted interfaces such as SQL to facilitate onboard processing of operational and scientific data, ODIS can dramatically increase the scientific yield of future missions. Technologies that use machine learning and spacecraft autonomy will especially benefit from ODIS as data is essential to machine learning implementations. Investing in this capability now and demonstrating in compliance with cFS FSW architecture will accelerate development of autonomous and flexible software and avert a future with differing, incompatible, and low performing architectures. nbsp;