Comprehensive engineering support spanning the entire lifecycle of remote sensing and imaging hardware and software systems.
- EO/IR Radiometric Calibration & Validation
Delivers end-to-end calibration and validation workflows for electro-optical and infrared systems, supporting both pre-launch instrument characterization and post-launch performance analysis.
- Integrated Space Systems Engineering
Provides systems engineering for space-based platforms, managing payload integration, quality assurance, and science traceability across Earth observation missions.
- Airborne Systems Integration (Manned & UAS)
Supports remote sensing strategies, sensor payload integration, flight testing, and field validation across high-altitude manned aircraft and unmanned aerial systems.
- Image Chain Analysis
Models and analyzes the entire path of sensor data from photon collection to final imagery to optimize system performance and data quality.
- System Design & Performance Characterization
Architects advanced remote sensing systems and evaluates operational performance through physics-based modeling and field validation campaigns.
- Modeling & Simulation
Tests and refines complex sensor behaviors and mission scenarios using predictive simulations to mitigate risk before hardware deployment.
- Instrument Science
Supports the full lifecycle of remote sensing instruments, from early-stage conceptual design and component testing to integration and operations.
- System Optimization
Enhances platform utility through design refinement, routine post-launch monitoring, trending analytics, and data reprocessing workflows.
- Feasibility Demonstration
Validates new sensing technologies and concepts via rapid prototyping, proof-of-concept system builds, and operational field trials.
- Mission Planning & Execution
Coordinates flight operations, logistics, payload preparation, and real-time support for airborne and spaceborne science campaigns.
- Data Collection & Analysis
Acquires, calibrates, and processes scientific data using advanced sensor systems and automated, AI-enhanced analytics workflows.
- System-of-Systems Architecture
Integrates disparate subsystems into unified configurations, ensuring secure data flow, interoperability, and system-wide performance control.
- AWS Cloud Computing for Remote Sensing Workflows
Deploys scalable, cloud-native geospatial pipelines and AI-ready environments to migrate, store, and process massive remote sensing datasets.
- Cloud-Based Solutions
Builds custom, secure cloud platforms and intuitive dashboards that integrate multi-domain environmental data feeds for decision-makers.