# Validation Log

## Validation Scenario 1: Normal Flight (80% of time)
UAV flies straight, consecutive frames overlap ~70-80%. Terrain has moderate texture (agricultural + urban mix).

### Expected Based on Conclusions
- XFeat extracts features in ~5ms, VO matching in ~20ms
- Satellite matching succeeds: coarse retrieval ~50ms, fine matching ~300ms
- ESKF fuses both: position accuracy ~10-20m (satellite-anchored)
- Total processing: <500ms per frame
- Confidence: HIGH

### Actual Validation (against literature)
SatLoc reports <15m error with >90% coverage under similar conditions. Mateos-Ramirez reports 0.83% drift with satellite correction. Both align with our expected performance.

### Result: ✅ PASS

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## Validation Scenario 2: Sharp Turn (5-10% of time)
UAV makes a 60-degree turn. Next frame has <5% overlap with previous. Heading changes rapidly.

### Expected Based on Conclusions
- VO fails (insufficient feature overlap) — detected by low match count
- IMU provides heading and approximate displacement for ~1-2 frames
- Satellite matching attempts independent localization of the new frame
- If satellite match succeeds: position recovered, segment continues
- If satellite match fails: IMU dead-reckoning with LOW confidence

### Potential Issues
- Satellite matching may also fail if the frame is heavily tilted (non-nadir view during turn)
- IMU drift during turn: at 100m/s for 1s, displacement ~100m. IMU drift over 1s: ~1-5m — acceptable

### Result: ⚠️ CONDITIONAL PASS — depends on satellite matching success during turn. Non-stabilized camera may produce tilted images that are harder to match. IMU provides reasonable bridge.

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## Validation Scenario 3: Disconnected Route (rare, <5%)
UAV completes segment A, makes a 90+ degree turn, flies a new heading. Segment B has no overlap with segment A. Multiple such segments possible.

### Expected Based on Conclusions
- Each segment independently localizes via satellite matching
- No explicit reconnection needed — all in WGS84 frame
- Per-segment accuracy depends on satellite matching success rate
- Low-confidence gaps between segments until satellite match succeeds

### Result: ✅ PASS — architecture handles this natively via independent per-frame satellite matching.

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## Validation Scenario 4: Memory-Constrained Operation (always)
3000 frames, 8GB shared memory. Full pipeline running.

### Expected Based on Conclusions
- Downsampled frame: ~5MB per frame. Keep 2 in memory (current + previous): ~10MB
- XFeat model (TensorRT): ~50-100MB
- Satellite tile features (loaded tiles): ~200-500MB for tiles near current position
- ESKF state: <1MB
- OS + runtime: ~1.5GB
- Total: ~2-3GB active, well within 8GB

### Potential Issues
- Satellite feature DB for large operational areas could be large on disk (not memory — loaded on demand)
- Need careful management of tile loading/unloading

### Result: ✅ PASS — 8GB is sufficient with proper memory management.

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## Validation Scenario 5: Degraded Satellite Imagery
Google Maps tiles at 0.5-1.0 m/px resolution. Some areas have outdated imagery. Seasonal appearance changes.

### Expected Based on Conclusions
- Coarse retrieval (global descriptors) should handle moderate appearance changes
- Fine matching may fail on outdated/seasonal tiles — confidence drops to LOW
- System falls back to VO + IMU in degraded areas
- Multiple consecutive failures → user input request

### Potential Issues
- If large areas have degraded satellite imagery, the system may operate mostly in VO+IMU mode with significant drift
- 50m accuracy target may not be achievable in these areas

### Result: ⚠️ CONDITIONAL PASS — system degrades gracefully, but accuracy targets depend on satellite quality. This is a known risk per Phase 1 assessment.

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## Review Checklist
- [x] Draft conclusions consistent with fact cards
- [x] No important dimensions missed
- [x] No over-extrapolation
- [x] Conclusions actionable/verifiable
- [x] Sharp turn handling addressed
- [x] Memory constraints validated
- [ ] Issue: Satellite imagery quality in eastern Ukraine remains a risk
- [ ] Issue: Non-stabilized camera during turns may degrade satellite matching

## Conclusions Requiring No Revision
All major architectural decisions validated. Two known risks (satellite quality, non-stabilized camera during turns) are acknowledged and handled by the fallback hierarchy.
