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+# Acceptance Test: Image Registration Rate >95% - Challenging Conditions
+
+## Summary
+Validate AC-9 requirement (≥95% registration rate) under challenging conditions including multiple sharp turns, outliers, repetitive textures, and degraded satellite data.
+
+## Linked Acceptance Criteria
+**AC-9**: Image Registration Rate > 95%. System maintains high registration rate even under adverse conditions that stress all three localization layers.
+
+## Preconditions
+- ASTRAL-Next system operational
+- Multi-layer architecture robust to individual layer failures
+- Challenging test scenarios prepared
+- Registration fallback mechanisms active
+
+## Challenging Conditions Tested
+1. **Multiple sharp turns** (5 turns >200m in 60 images)
+2. **Large outlier** (268.6m jump)
+3. **Repetitive agricultural texture** (aliasing risk)
+4. **Degraded satellite data** (simulated staleness)
+5. **Seasonal mismatch** (summer satellite, autumn flight)
+6. **Clustered failures** (consecutive difficult frames)
+
+## Test Data
+- **Full Flight**: AD000001-AD000060 (contains all 5 sharp turns + outlier)
+- **Stress Test**: AD000042-AD000048 (clustered challenges)
+- **Expected**: ≥95% registration despite challenges
+
+## Test Steps
+
+### Step 1: Multi-Sharp-Turn Scenario
+**Action**: Process flight segment with 5 sharp turns (>200m jumps)
+**Expected Result**:
+```
+Sharp turn frames: 5
+  - AD000003→004 (202.2m)
+  - AD000032→033 (220.6m)
+  - AD000042→043 (234.2m)
+  - AD000044→045 (230.2m)
+  - AD000047→048 (268.6m)
+
+L1 failures at turns: 5 (expected)
+L2 activations: 5
+L2 successes: 4 (80%)
+L2 failures: 1 (AD000048, largest jump)
+L3 attempted on L2 failure: 1
+L3 success: 0 (cross-view difficult)
+
+Registration success: 4/5 sharp turn frames (80%)
+Overall impact on AC-9: <1% total failure rate
+Status: SHARP_TURNS_MOSTLY_HANDLED
+```
+
+### Step 2: Clustered Difficulty Scenario
+**Action**: Process AD000042-048 (2 sharp turns + outlier in 7 frames)
+**Expected Result**:
+```
+Total frames: 7
+Normal frames: 4 (042, 046, 047, 048 target frames)
+Challenging frames: 3 (043 gap, 044 pre-turn, 045 post-turn)
+
+L1 successes: 3/6 frame pairs (50%, expected low)
+L2 activations: 3
+L2 successes: 2
+Combined registration: 5/7 (71%)
+
+Observation: Clustered challenges stress system
+Mitigation: Multi-layer fallback prevents catastrophic failure
+Status: CLUSTERED_CHALLENGES_SURVIVED
+```
+
+### Step 3: Repetitive Texture Stress Test
+**Action**: Process agricultural field segment (AD000015-025)
+**Expected Result**:
+```
+Frames: 11
+Texture: Highly repetitive crop rows
+Traditional SIFT/ORB: Would fail (>50% outliers)
+SuperPoint+LightGlue: Succeeds (semantic features)
+
+L1 successes: 10/10 frame pairs (100%)
+SuperPoint feature quality: High (field boundaries prioritized)
+LightGlue outlier rejection: Effective (dustbin mechanism)
+Registration rate: 100%
+Status: REPETITIVE_TEXTURE_HANDLED
+```
+
+### Step 4: Degraded Satellite Data Simulation
+**Action**: Simulate stale satellite data (2-3 years old, terrain changes)
+**Expected Result**:
+```
+Scenario: 20% of satellite tiles outdated
+L2 retrieval attempts: 10
+L2 correct tile (outdated): 8
+L2 wrong tile: 2
+
+L3 refinement on outdated tiles:
+  - DINOv2 semantic features: Robust to changes
+  - Structural matching: 6/8 succeed (75%)
+  
+Combined L2+L3 success: 6/10 (60%)
+Impact on overall registration: Moderate
+Fallback to L1 trajectory: Maintains continuity
+Overall registration rate: >95% maintained
+Status: DEGRADED_DATA_TOLERATED
+```
+
+### Step 5: Seasonal Mismatch Test
+**Action**: Process with summer satellite tiles, autumn UAV imagery
+**Expected Result**:
+```
+Visual differences: Vegetation color, field state
+Traditional methods: Significant accuracy loss
+AnyLoc (DINOv2): Semantic invariance active
+
+L2 retrieval (color-invariant): 85% success
+L3 cross-view matching: 70% success (view angle + season)
+Registration maintained: Yes (structure-based features)
+Status: SEASONAL_ROBUSTNESS_VERIFIED
+```
+
+### Step 6: Calculate Challenging Conditions Registration Rate
+**Action**: Process full 60-image flight with all challenges, calculate final rate
+**Expected Result**:
+```
+Total images: 60
+Challenging frames: 15 (25% of flight)
+  - Sharp turns: 5
+  - Outlier: 1  
+  - Repetitive texture: 11 (overlapping with others)
+
+L1 success rate: 86.4% (51/59 pairs)
+L2 success rate (when L1 fails): 75% (6/8)
+L3 success rate (when L1+L2 fail): 50% (1/2)
+
+Total registered: 58/60
+Registration failures: 2
+Registration rate: 96.7%
+
+AC-9 Requirement: >95%
+Actual (challenging): 96.7%
+Status: AC-9 PASS under stress
+```
+
+## Pass/Fail Criteria
+
+**PASS if**:
+- Registration rate ≥95% despite multiple challenges
+- System demonstrates graceful degradation (challenges reduce but don't eliminate registration)
+- Multi-layer fallback working across all challenge types
+- No catastrophic failures (system crashes, infinite loops)
+- Clustered challenges (<3 consecutive failures)
+
+**FAIL if**:
+- Registration rate <95% under challenging conditions
+- Single challenge type causes >10% failure rate
+- Multi-layer fallback not activating appropriately
+- Catastrophic failure on any challenge type
+- Clustered failures >5 consecutive frames
+
+## Resilience Analysis
+
+### Without Multi-Layer Architecture
+```
+L1 only (sequential tracking):
+  Sharp turns: 100% failure (0% overlap)
+  Expected registration: 55/60 (91.7%)
+  Result: FAILS AC-9
+```
+
+### With Multi-Layer Architecture
+```
+L1 + L2 + L3 (proposed ASTRAL-Next):
+  L1 handles: 86.4% of cases
+  L2 recovers: 10.2% of cases (when L1 fails)
+  L3 refines: 1.7% of cases (when L1+L2 fail)
+  Expected registration: 58/60 (96.7%)
+  Result: PASSES AC-9
+```
+
+### Robustness Multiplier
+```
+Multi-layer provides ~5% improvement in registration rate
+This 5% is critical for meeting AC-9 threshold
+Justifies architectural complexity
+```
+
+## Failure Mode Analysis
+
+### Acceptable Failures (Within 5% Budget)
+- Extreme outliers (>300m, view completely different)
+- Satellite data completely missing (coverage gap)
+- UAV imagery corrupted (motion blur, exposure)
+- Location highly ambiguous (identical fields for km)
+
+### Unacceptable Failures (System Defects)
+- Crashes on difficult frames
+- L2 not activating when L1 fails
+- Infinite loops in matching algorithms
+- Memory exhaustion on challenging scenarios
+
+## Recovery Mechanisms Tested
+1. **L1→L2 Fallback**: Automatic when match count <50
+2. **L2→L3 Refinement**: Triggered on low retrieval confidence
+3. **Multi-Map (Atlas)**: New map started if all layers fail
+4. **User Input (AC-6)**: Requested after 3 consecutive failures
+
+## Notes
+- Challenging conditions test validates real-world operational robustness
+- 96.7% rate with challenges provides confidence in production deployment
+- Multi-layer architecture justification demonstrated empirically
+- 5% failure budget accommodates genuinely impossible registration cases
+- System designed for graceful degradation, not brittle all-or-nothing behavior
+