The revised IR model exposes more dim targets and more ambiguous clutter.
Dim-target recall protects the field objective, while restrained classifications protect tracking and autonomy behavior.
Who you’d be doing this for
“I need one answer on what the aircraft will call a target, not three interpretations after the flight.”
Huong Rattanakorn · Autonomy Program Manager
Responsible for presenting test evidence and field readiness for an unmanned-system program.
What is at stake
The revised model improves dim-target recall but increases clutter classifications during HIL runs. You must weigh field detection gains against the tracking and autonomy consequences of a committed release.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- dim-target recall vs clutter classifications
- offline gains vs HIL behavior
- flight-window certainty vs deeper verification
- perception capability vs downstream track stability
Why Applied Intuition
Jetson Orin+ deployment connects perception evidence to the live unmanned-system demonstrations this defense autonomy toolchain supports.
Written with these in mind
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This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.