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Here's what ChatGPT had to say about it:

The Gremlin system includes hyperspectral imaging, radar systems, and thermal imaging as part of its sensor suite. These technologies allow it to detect, analyze, and differentiate between various types of objects, including solid physical entities and phenomena like light or plasma.
Here’s how each component contributes:
1. Hyperspectral Imaging
Purpose: Captures data across a wide range of electromagnetic wavelengths, beyond just visible light. Capability: Identifies materials and surface properties of objects by analyzing how they reflect or absorb light across different spectra (e.g., infrared, ultraviolet). Use for UAPs: Distinguishes between physical objects and non-solid phenomena, such as reflections, plasma, or light projections.
2. Radar Systems (2D and 3D)
Purpose: Uses radio waves to measure the distance, speed, and size of an object.
Capability: Creates a detailed spatial map of the object's structure and movement patterns.
Use for UAPs: Confirms the physical presence of objects and tracks their motion, distinguishing solid entities from light phenomena that don’t reflect radar signals in the same way.
3. Thermal Imaging
Purpose: Detects heat signatures emitted by objects. Capability: Determines whether an object is radiating heat (as a solid object might) or is a cooler light-based phenomenon.
Use for UAPs: Differentiates between objects with thermal mass (e.g., vehicles, drones) and non-solid entities or atmospheric effects.
Integration and Advanced Analysis
The combination of these systems allows the Gremlin to:
Collect comprehensive data across multiple domains (air, space, and sea).
Cross-correlate sensor readings to improve accuracy.
Reduce ambiguity by providing a multidimensional profile of detected objects.
Conclusion
The inclusion of hyperspectral imaging, radar, and thermal sensors equips the Gremlin system to analyze UAPs with exceptional precision, making it one of the most advanced tools for investigating such phenomena.