CubeSat Flight Software & Guidance, Navigation, and Control (GNC)

Modular CubeSat Flight Software and GNC Framework for Autonomous Spacecraft Operations

A high-performance C++ Flight Software (FSW) and GNC simulation framework for CubeSats. Designed for transitioning from pure software simulation to hardware-in-the-loop (HIL) readiness.

Detailed Documentation

For in-depth explanations of the system's logic and algorithms, refer to:

• Architecture Overview: Modular design, task scheduling, and state management.
• Attitude Estimation (MEKF): Multiplicative EKF implementation and noise modeling.
• Attitude Control: B-dot detumbling and 3-axis PID pointing laws.
• FDIR System: Fault Detection, Isolation, and Recovery strategies.

System Architecture

graph TD
    Sensors -->|Raw Data| SE[State Estimation]
    SE -->|Estimated State| Guidance
    Guidance -->|Targets| Control
    Control -->|Commands| Dynamics
    SE -.->|Health Status| FDIR[FDIR System]
    FDIR -->|Recovery Actions| MM[Mode Manager / Flight Executive]
    MM -->|Telem Packets| Ground[Telemetry & Ground Interface]

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Mission Showcase

The system demonstrates a complete autonomous CubeSat mission from deployment through science operations to ground communication. The visualization below shows a full 60-minute mission timeline with real-time telemetry across all subsystems.

Mission Overview

1. Orbital Dynamics

The simulation propagates a realistic Low Earth Orbit (LEO) trajectory:

• Altitude: ~400 km (International Space Station orbit)
• Inclination: 51.6°
• Perturbations: J2 zonal harmonic effects included
• Ground Track: Shows global coverage over the 1-hour mission duration

2. Attitude Control & Detumbling

Deployment Phase (0-2 min):

• Initial tumble rate: 0.12 rad/s (~7 deg/s)
• B-Dot Controller (Red trace) rapidly detumbles the spacecraft using magnetorquers
• Stabilization achieved in <2 minutes

3. GNC Performance

Pointing Accuracy:

• NOMINAL Mode (Cyan): Sun-pointing with <1° error
• SCIENCE Mode (Blue): Precise target tracking with <0.5° error
• DOWNLINK Mode (Green): Ground station pointing
• Reaction Wheels: Momentum is managed comfortably within limits (no saturation)

4. Autonomous Mission Timeline

The Mode Manager autonomously drives the mission state machine, supporting key Mission Scenarios:

1. Detumbling (B-dot): Rapid stabilization after deployment in SAFE Mode.
2. Sun Pointing: Maximize power generation in NOMINAL Mode.
3. Nadir Pointing / Science: High-precision target tracking in SCIENCE Mode.
4. Fault Recovery: Autonomous transition to SAFE mode upon fault detection and subsequent Recovery.

Mission Statistics (1 Hour Run):

• Duration: 60 minutes
• Data Collected: >10 units
• Data Downlinked: >10 units (100% throughput)
• Mode Transitions: 3 autonomous transitions verified

Key Features

• Estimation & Navigation: Multiplicative Extended Kalman Filter (MEKF) fusing Magnetometer, Sun Sensor, and Star Tracker data.
• Control Laws:
  • B-Dot: Magnetic detumbling for safe-mode operations.
  • PID & LQG: Precision 3-axis pointing control using Reaction Wheels.
  • Wheel Desaturation: Momentum management using magnetorquers.
• FDIR (Fault Detection, Isolation, and Recovery): Sensor health monitoring and automatic mode switching logic.
• Flight Executive: Task scheduling, state machine management, and robust command parsing.
• Communication: CCSDS Telemetry packet encoding for attitude, orbit, and health data.
• High-Performance Core:
  • Lock-Free Communication: Single-Producer Single-Consumer (SPSC) message bus for ultra-low latency inter-task telemetry.
  • SIMD-Optimized State Management: Structure-of-Arrays (SoA) memory layout for batch state processing using Eigen vectorization.
• Simulation Engine:
  • High-fidelity rigid body dynamics (Euler's equations) with RK4 integration.
  • J2 Perturbation orbit propagation.
  • Realistic sensor/actuator models with noise and latency.
• Mission Visualization:
  • Comprehensive Dashboard: 12-panel unified view of all mission aspects.
  • 3D Trajectory & Ground Track: Interactive orbit and 2D map projections.

Project Structure

├── src/
│   ├── common/         # Math types, StateHistory (SoA), profiler and logging
│   ├── fsw/            # Flight Software core
│   │   ├── core/       # DataStore, ModeManager, SPSCQueue, TaskScheduler
│   │   ├── gnc/        # MEKF, PID, B-Dot, Pointing Strategies
│   │   ├── fdir/       # Fault Detection and Recovery
│   │   └── telemetry/  # CCSDS Telemetry Encoding
│   ├── hal/            # Hardware Abstraction Layer interfaces
│   ├── sim/            # Simulation engine, hardware models, and Ground Station
│   └── opt/            # Optimization tools (Genetic Algorithms)
├── tests/              # Unit tests and integration/mission demos
├── python/             # Visualization and analysis tools
│   ├── visualize_mission.py    # Unified mission dashboard
│   ├── data_loader.py          # Data extraction utilities
│   └── README.md               # Detailed usage guide

Getting Started

Prerequisites

• CMake (>= 3.16)
• C++17 Compiler (GCC/Clang/MSVC)
• Python 3.8+ (for visualization)
• Dependencies (Automated via CMake): Eigen, spdlog, googletest

Build Instructions

mkdir build
cd build
cmake ..
cmake --build . --config Release

Running the Mission Simulation

cd build
.\tests\Release\mission_test.exe --gtest_filter=MissionTest.FullMissionSimulation

Output: Generates mission_data.csv with 31 columns of telemetry:

• Basic state: time, quaternion, rates, position, velocity, mode
• GNC control: commanded/external torques, target attitude, pointing error, momentum
• Mission progress: data collected, data downlinked

Visualizing Mission Results

# From project root
# Install Python dependencies (first time only)
python -m pip install -r python/requirements.txt

# Create interactive dashboard
python python/visualize_mission.py build/mission_data.csv

# Or save to PNG
python python/visualize_mission.py build/mission_data.csv --save

Output: build/mission_dashboard.png - Comprehensive 12-panel visualization

See python/README.md for detailed visualization documentation.

Understanding the Dashboard

The mission dashboard provides complete observability:

Orbital Dynamics (Row 1):

• Left: 3D trajectory colored by mission mode
• Center: Ground track showing satellite path over Earth
• Right: Orbital elements (SMA and inclination vs time)

Attitude Dynamics (Row 2):

• Left: 3D body frame visualization (final state)
• Center: Quaternion components showing smooth attitude evolution
• Right: Angular rates with detumble visible in first 80 seconds

GNC Performance (Row 3):

• Left: Pointing error - spikes during slew maneuvers, convergence in each mode
• Center: Control torques - B-dot (external) in SAFE, PID (commanded) in other modes
• Right: Reaction wheel momentum buildup from control activity

Mission Progress (Row 4):

• Left: Mode timeline with color-coded phases
• Center: Data collection during SCIENCE, downlink during DOWNLINK
• Right: Mission statistics summary (orbit, attitude, data metrics)

Future Roadmap (Upcoming Phases)

Extended Mission Scenarios

• Constellation Support: Multi-satellite coordination.
• Eclipse Modeling: Power-constrained operations.
• Advanced FDIR: Sensor failure recovery demonstrations.

Virtual HIL

• Virtual Bus Interface: Implement a virtual I2C/SPI interface.
• Virtual Sensors: Implement a virtual sensor interface with quantization.
• Virtual Driver: Implement a driver for FSW, virtual MPU6050.

Developed for advanced CubeSat mission modeling and flight software development.

License

MIT License. See LICENSE for details.

Author

Batuhan Akkova
Email