Hyperspectral and Multispectral Systems Engineering Training by Tonex
This course offers a systems engineering perspective on hyperspectral and multispectral technologies, focusing on the design, development, and deployment of these sensing systems. It is tailored for engineers, scientists, and technical professionals interested in understanding the full lifecycle of spectral systems, from concept to application.
Learning Objectives
Participants will:
- Understand the principles of hyperspectral and multispectral system design
- Be familiar with the engineering trade-offs in system development
- Gain insights into data acquisition, processing, and system integration
- Learn about the latest trends and technologies in spectral systems engineering
Target Audience:
- Engineers and technical professionals in aerospace, defense, and geospatial industries
- Scientists and researchers involved in remote sensing and system design
- Academics in systems engineering and related fields
Prerequisites:
- Background in engineering, physics, or computer science is recommended.
Course outlines:
Day 1: Foundations of Hyperspectral and Multispectral Systems
Session 1: Overview of Spectral Sensing Systems
- Introduction to hyperspectral and multispectral sensing systems
- Differences in spectral, spatial, and temporal resolutions
- Key applications driving system requirements
- Overview of sensing platforms (satellites, UAVs, and ground-based systems)
Session 2: Spectral Sensor Design and Development
- Principles of sensor design (optics, detectors, and calibration)
- Imaging spectrometers: Pushbroom, whiskbroom, and snapshot techniques
- Spectral and spatial resolution trade-offs
- Sensor material considerations: CCD, CMOS, and thermal sensors
Session 3: Data Acquisition Systems
- Signal processing fundamentals
- Role of hardware and firmware in spectral data acquisition
- Noise management and system calibration techniques
- Integration of sensors with platforms and data storage systems
Session 4: Systems Engineering Framework
- Introduction to systems engineering for spectral sensing
- Requirements definition and trade studies
- System lifecycle: Concept, development, deployment, and operation
- Risk analysis and mitigation strategies
Day 2: Advanced Concepts and Applications
Session 5: Data Processing and Analytics Pipeline
- Onboard vs. ground-based data processing
- Spectral unmixing and dimensionality reduction techniques
- Real-time data streaming and processing for operational systems
- Software considerations: Open-source tools and proprietary platforms
Session 6: System Integration and Testing
- Integration challenges for spectral systems on various platforms
- Validation and verification processes
- End-to-end system testing methodologies
- Case study: Designing a satellite-based hyperspectral system
Session 7: Applications and Mission Design
- Earth Observation: Environmental monitoring, agriculture, and water resources
- Military and Defense: Target detection, surveillance, and reconnaissance
- Space Exploration: Planetary mapping and mineral analysis
- Custom Applications: Industry-specific system design considerations
Session 8: Future Trends in Spectral Systems Engineering
- Advances in miniaturized sensors and high-performance optics
- Integration with machine learning, cloud computing, and IoT
- Emerging platforms: CubeSats, drones, and wearable devices
- Sustainability and cost-effective system design