End-to-End Ozone Mapping and Profiler Suite (OMPS) Mission Data Modeling and Simulation

1. End-to-End Ozone Mapping and Profiler Suite (OMPS) Mission Data Modeling and Simulation Angela Li, Jizhong Chen*, Gary Smith, Lesyle Boyce, Christopher Roberts NASA Goddard Space Flight Center, Software Engineering Division, Mail Code 474.0 *Columbus Technologies and Services Pending NASA Code 500 Review

2. Benefits • Requirements traceability to design, code and test in integrated environment • Consistent architecture, design, code and documentation of both Flight and Ground Software Subsystems • Reverse engineer C, C++ or Java code for capturing existing Flight and Ground systems developed without a standardized methodology • Facilitates automated Verification and Validation(V&V) and gap analysis through the use of model checking tools

3. Benefits (Continued…) • Full behavioral code generation for C, C++ and Java applications targeting real-time operating systems • Interface Definition and Management • System -to- System and External Interfaces • Verification of information flow between key Interfaces • SysML provides flexible allocation tables that supports requirements allocation, functional allocation, and structural allocation • SysML provides linkage with DoDAF, MODAF or UPDM support

4. JPSS Context Diagram March 2, 2011 JPSS Program • Cross Support • Flight Segment • DMSG – DMSP-x • JAXA – GCOM-x • EUMETSAT – METOP-x • DMSG – DWSS-x • NRL – WINDSAT • NASA – NPP JPSS Flight Projects • JPSS-1 • JPSS-2 • Free Flyer • TSIS FF • Services FF • SARSAT • A-DCS • NPP (Instruments) • JPSS Ground Project • Flight Operations – • NPP, JPSS, DWSS, Free Flyer • Data Acquisition Product Generation and Distribution • NPP, JPSS, DWSS, GCOM, Free Flyer • Data Acquisition and Routing Only • DMSP, METOP, WINDSAT • External NOAA Organizations • OSPO • STAR • Climate Service • OSD • NWS • Customers • IDPS Consumers – AFWA, FNMOC, NAVO, NESDIS/NDE, CLASS • - National Weather Service, USDA, EPA, Agriculture, Fisheries, DoD Branches of Service etc. • Direct Readout Consumers – • Civilian, Military, Int’l • Search and Rescue • External NASA • Organizations • \ • Launch Services Program (LSP) • Near Earth Network (NEN) • Space Network (SN) • Flight Dynamics Facility (FDF) • NASA Science Data Segment (SDS) - NPP Only • LaRC for CERES Development • Cross Support • Ground Systems • JAXA Ops • EUMETSAT Ops • AFSCN

5. JPSS Ground System Operational Flows OV-1 SDS (NPP) DMSP Ops (NOAA / 6 SOPS) CLASS (NOAA) Coriolis Ops (AFSPC) Field Terminal Users Launch Support, Commissioning & Contingency March 2, 2011 GPS GCOM-n JPSS-n WindSat / Coriolis NPP TDRSS (Example of Use) DWSS-n DMSP-n Free Flyers*: TSIS/A-DCS/ SARSAT MetOp-n L/X-Band X-Band L/X-Band X-Band Field Terminals X-Band S-Band Provides Mission Planning, Spacecraft Control, Data Acquisition, Routing, and Processing, Product Generation and Distribution, Calibration, Validation, and Enterprise Management Ka-Band Ka-Band GCOM @ KSAT X-Band DR Terminals GCOM SMD WSC X-Band NASA @ McMurdo MSD functions FDF Joint Polar Satellite System (JPSS) Ground System Security GCOM Ops (JAXA) EUMETSAT Algorithm Updates DMSP DP (AFWA) NAVO NSA FNMOC STAR (NOAA) NWS TOC (NOAA) AFWA Launch Support NESDIS/ NDE (NOAA) WindSat DP (NRL/ FNMOC) * Implementation dependent Ancillary Data, ODAD, SDAD, CODAD Argos Beacon / HK Data/ SARSAT GPS Crypto Keys Telemetry Tracking & Control HRD LRD MSD Retain Intermediate product (RIP) Mission Support Data Data Quality Report Legend: Backup TT&C xDRs / Metadata Operations Coordination Stored Mission Data

6. Mission Data Formats The Consultative Committee for Space Data Systems (CCSDS) Packet Multiplexing Protocol Data Unit (MPDU) Coded Virtual Channel Data Unit (CVCDU) Channel Access Data Unit (CADU) Raw Data Record (RDR) Science Data Record (SDR) Environmental Data Record (EDR) Intermediate Product (IP)

7. OMPS Total Column Data Flow

8. Strategies • Rapid prototyping of behavioral model • Enable early proof of concept and requirement verification and validatin • Leverages NASA reusable assets to rapidly create executable models • Provides simulation of the runtime environments • Verify adequacy of real-time performance requirements • Provides capability for early detection and isolation of potential data flow bottleneck • Providing a model view of the system that is scalable to simulate worst case demand loading

9. Strategies (Continued…) • Document the format and timing of information flows between systems and/or subsystems in standardized graphical format • Provide automated interface-to-interface verification and validation • Support subsystem testing and verification • By providing high fidelity modeling of external stimulus to the unit-under-test in a controlled environment

10. Approaches • Flight Vehicle Test Suite (FVTS) • Hardware based Engineering Model (EM) class • Software or COTS hardware based Operations (OPS) class • End-to-End Data Modeling • Capture data format change from CCSDS packet to CADU • Use UML tools • Generate code for simulation • Verify the FVTS simulation results independently • Object Oriented (OO) model • Easy to extend • Data driven simulation

11. OMPS Class Diagram

12. OMPS Sequence Diagram

13. Path Forward Integrate the model with an XML Parser Initialize the model with real OMPS science RDR files – Done Run the Simulation from Packet to CADU Make the model simulation data driven Run simulation side-by-side with FVTS Or feed the simulation data into FVTS

14. Summary • OMPS End-to-end Data Modeling provide us a clear, visual way to understand mission science data format • The Simulation capability of the data model provide us a way to inject real science data into FVTS • The object oriented nature of the model is very easy to be extended to any instrument, any data product, including: • Spacecraft house keeping • Instrument calibration

15. Acknowledgement Holly Abraham – Columbus Technologies and Services Brett Mathews - Columbus Technologies and Services Larry Barrett – Orbital Science Corp. Richard Cember – Computational Physics Inc. Timothy Dorman – Computational Physics Inc.