Simulation Library for Autonomous and Collaborative Satellite Sensor Networks
Future Earth-observation missions will involve intelligent networks of diverse sensor platforms which coordinate to make Earth observations.
Small satellite constellations and new science instruments will facilitate high-density (faster revisit time) and multi-dimensional (temporal and spatial) measurements.
Collaborative communication is key to enabling coordinated observations.
Challenge – Adaptive remote sensing with constrained resources introduces a complex decision-making space.
Questions – How do we maximize the science return from measurements? How do we prepare for the next-generation of Earth observation missions?
Approach – New simulation tools – a software library for adaptive and collaborative observing-system simulation experiments (OSSEs).
New Software Library Features
- Rapid simulation development and constellation design
- Coordination among diverse sensor platforms
- Facilitate algorithm development (adaptive sensor reconfiguration, system resource management, delay-tolerant networking)
- Produce simulation data (events, telemetry, networking, etc.)
- Open-source, modular, and freely available for integration with larger OSSEs
Open Source (GPL) Software Package
Three Main Components
- C++ Library
- Code for developing novel observing-system simulation experiments
- C++ Example Programs
- Demonstrate library capabilities
- Execute these to produce Simulation Result Files
- Python Utilities
- Process Simulation Result Files → Analysis Files
- Open-source third-party packages (Pandas, Cartopy, NetCDF, Matplotlib, Numpy, etc.)
Functional Capabilities
- Use classes to create objects (object-oriented)
- Propagate physical position and orientation of satellites
- Model realistic communication links, routes, and sensing