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_docs/02_tests/45_registration_rate_baseline_spec.md

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+# Acceptance Test: Image Registration Rate >95% - Baseline
+
+## Summary
+Validate AC-9 requirement that ≥95% of images successfully register (find enough matching features for pose estimation) under normal flight conditions.
+
+## Linked Acceptance Criteria
+**AC-9**: Image Registration Rate > 95%. The system can find enough matching features to confidently calculate the camera's 6-DoF pose (position and orientation) and "stitch" that image into the final trajectory.
+
+## Preconditions
+- ASTRAL-Next system operational
+- Normal flight conditions (no extreme weather, lighting, or terrain)
+- Multi-layer architecture (L1, L2, L3) active
+- Registration success criteria defined
+
+## Registration Success Definition
+An image is **successfully registered** if:
+1. L1 sequential tracking succeeds (≥50 inlier matches), OR
+2. L2 global retrieval succeeds (correct satellite tile, confidence >0.6), OR
+3. L3 metric refinement succeeds (cross-view match confidence >0.5)
+
+An image **fails registration** only if ALL three layers fail.
+
+## Test Data
+- **Primary Dataset**: AD000001-AD000030 (baseline segment, normal conditions)
+- **Secondary Dataset**: AD000001-AD000060 (full flight, includes challenges)
+- **Expected**: ≥95% registration rate for both datasets
+
+## Test Steps
+
+### Step 1: Process Baseline Segment (Normal Conditions)
+**Action**: Process AD000001-AD000030, track registration outcomes
+**Expected Result**:
+```
+Total images: 30
+L1 successful: 28 (93.3%)
+L2 successful (L1 failed): 2 (6.7%)
+L3 successful (L1+L2 failed): 0 (0%)
+Total registered: 30 (100%)
+Registration rate: 100% > 95% (AC-9 PASS)
+Status: BASELINE_EXCELLENT
+```
+
+### Step 2: Analyze L1 Registration Performance
+**Action**: Examine L1 sequential tracking success rate
+**Expected Result**:
+```
+L1 attempts: 29 (frame-to-frame pairs)
+L1 successes: 28
+L1 failures: 1
+L1 success rate: 96.6%
+Failure case: AD000003→004 (202.2m jump, expected)
+L1 failure handling: L2 activated successfully
+Status: L1_BASELINE_PASS
+```
+
+### Step 3: Analyze L2 Fallback Performance
+**Action**: Examine L2 global retrieval when L1 fails
+**Expected Result**:
+```
+L2 activations: 2 (L1 failure triggers)
+L2 successes: 2
+L2 failures: 0
+L2 success rate: 100%
+Cases: AD000004 (after 202m jump), AD000033 (after 220m jump)
+L2 contribution: Prevented 2 registration failures
+Status: L2_FALLBACK_WORKING
+```
+
+### Step 4: Process Full Flight with Challenges
+**Action**: Process AD000001-AD000060, including sharp turns and outliers
+**Expected Result**:
+```
+Total images: 60
+L1 successful: 53 (88.3%)
+L2 successful (L1 failed): 6 (10%)
+L3 successful (L1+L2 failed): 0 (0%)
+Registration failures: 1 (1.7%)
+Registration rate: 98.3% > 95% (AC-9 PASS)
+Status: FULL_FLIGHT_PASS
+```
+
+### Step 5: Identify and Analyze Registration Failures
+**Action**: Investigate any frames that failed all three registration layers
+**Expected Result**:
+```
+Failed frame: AD000048 (hypothetical example)
+L1 failure: 268.6m jump from AD000047, overlap ~0%
+L2 failure: Satellite data outdated, wrong tile retrieved
+L3 failure: Cross-view match confidence 0.3 (below 0.5 threshold)
+Outcome: User intervention requested (AC-6 human-in-the-loop)
+Acceptable: <5% failure rate allows for extremely difficult cases
+Status: FAILURE_WITHIN_TOLERANCE
+```
+
+### Step 6: Calculate Final Registration Statistics
+**Action**: Compute comprehensive registration metrics
+**Expected Result**:
+```
+Dataset: AD000001-060 (60 images)
+Successfully registered: 59 images
+Registration failures: 1 image
+Registration rate: 98.3%
+
+AC-9 Requirement: >95%
+Actual Performance: 98.3%
+Margin: +3.3 percentage points
+Status: AC-9 PASS with margin
+```
+
+## Pass/Fail Criteria
+
+**PASS if**:
+- Registration rate ≥95% on baseline dataset (AD000001-030)
+- Registration rate ≥95% on full flight dataset (AD000001-060)
+- Multi-layer fallback working (L2 activates when L1 fails)
+- Registration failures <5% (allowing for extremely difficult frames)
+
+**FAIL if**:
+- Registration rate <95% on either dataset
+- L2 fallback not activating when L1 fails
+- Registration failures >5%
+- System crashes on unregistered frames (should handle gracefully)
+
+## Layer Contribution Analysis
+
+### Layer 1 (Sequential Tracking)
+- **Role**: Primary registration method (fastest)
+- **Success Rate**: 85-95% (normal overlap conditions)
+- **Failure Cases**: Sharp turns, low overlap
+
+### Layer 2 (Global Retrieval)
+- **Role**: Fallback for L1 failures (slower but robust)
+- **Success Rate**: 85-95% when activated
+- **Failure Cases**: Stale satellite data, ambiguous locations
+
+### Layer 3 (Metric Refinement)
+- **Role**: Precision improvement, not primary registration
+- **Success Rate**: 80-90% when attempted
+- **Failure Cases**: Large view angle difference, seasonal mismatch
+
+### Multi-Layer Defense
+```
+Registration Success = L1 OR L2 OR L3
+P(success) = 1 - P(all fail)
+P(success) = 1 - (0.10 × 0.10 × 0.15)
+P(success) = 1 - 0.0015
+P(success) = 99.85% > 95% (AC-9)
+```
+
+## Registration Failure Handling
+When registration fails for a frame:
+1. System flags frame as UNREGISTERED
+2. Continues processing subsequent frames
+3. Attempts to re-register after later frames provide context
+4. If still fails after 3 attempts, requests user input (AC-6)
+5. Does not crash or halt processing
+
+## Quality Metrics Beyond Registration Rate
+- **Mean inlier count**: >100 matches (L1 successful cases)
+- **Mean confidence**: >0.8 (registered frames)
+- **Pose covariance**: <50m uncertainty (registered frames)
+- **Trajectory continuity**: No gaps >3 frames
+
+## Notes
+- AC-9 threshold of 95% balances operational utility with real-world challenges
+- 5% failure allowance (~3 frames per 60) accommodates extreme cases
+- Multi-layer architecture critical for achieving high registration rate
+- "Atlas" multi-map approach counts disconnected fragments as registered
+- Registration rate > positioning accuracy (AC-1/AC-2) requirements
+