refactor(01-01): convert hot-path schemas/*.py to hot_types re-export shims

- schemas/eskf.py: keep ConfidenceTier + ESKFConfig; re-export IMUSample
  and ESKFState from hot_types (define ConfidenceTier BEFORE the
  hot_types imports to avoid circular import — eskf_state.py imports
  ConfidenceTier from this module). Legacy alias IMUMeasurement = IMUSample.
- schemas/vo.py: re-export Features, Matches, RelativePose, Motion,
  VOEstimate from hot_types.vo_estimate.
- schemas/satellite.py: re-export TileCoords, TileBounds, SatelliteAnchor.
- schemas/metric.py: keep LiteSAMConfig; re-export AlignmentResult,
  ChunkAlignmentResult, Sim3Transform.
- schemas/rotation.py: keep HeadingHistory + RotationConfig; re-export
  RotationResult.

Auto-fixes (Rules 1 + 3) needed to keep the 216-test floor green:
- core/rotation.py: refactor try_rotation_steps to use
  dataclasses.replace instead of attribute assignment on RotationResult
  (Rule 1 — frozen dataclass forbids mutation; Pydantic silently allowed
  it). PATTERNS.md §6.1 already flagged Pose mutation but missed this site.
- hot_types/vo_estimate.py: add Optional `covariance: np.ndarray` field
  to RelativePose (Rule 3 — five test sites construct RelativePose with
  `covariance=np.eye(6)`; Pydantic v2 silently accepted the extra kwarg
  via default `extra="ignore"`. Declaring the field preserves the
  construction contract under the dataclass migration without editing
  tests).

Verification: pytest tests/ -q --ignore=tests/e2e → 216 passed, 8 skipped
(matches baseline). Accuracy bench (23 tests) passes.

src/gps_denied/schemas/metric.py

@@ -1,46 +1,17 @@
-"""Metric Refinement schemas (Component F09)."""
+"""Metric Refinement schemas (Component F09).
 
+Phase 1 shim — hot-path types `AlignmentResult`, `ChunkAlignmentResult`,
+`Sim3Transform` live in `gps_denied.hot_types.alignment_result`.
+`LiteSAMConfig` (config) stays here as a Pydantic boundary type.
+"""
 
-import numpy as np
 from pydantic import BaseModel
 
-from gps_denied.schemas import GPSPoint
-
-
-class AlignmentResult(BaseModel):
-    """Result of aligning a UAV image to a single satellite tile."""
-    model_config = {"arbitrary_types_allowed": True}
-
-    matched: bool
-    homography: np.ndarray  # (3, 3)
-    gps_center: GPSPoint
-    confidence: float
-    inlier_count: int
-    total_correspondences: int
-    reprojection_error: float  # Mean error in pixels
-
-
-class Sim3Transform(BaseModel):
-    """Sim(3) transformation: scale, rotation, translation."""
-    model_config = {"arbitrary_types_allowed": True}
-
-    translation: np.ndarray  # (3,)
-    rotation: np.ndarray  # (3, 3) rotation matrix
-    scale: float
-
-
-class ChunkAlignmentResult(BaseModel):
-    """Result of aligning a chunk array of UAV images to a satellite tile."""
-    model_config = {"arbitrary_types_allowed": True}
-
-    matched: bool
-    chunk_id: str
-    chunk_center_gps: GPSPoint
-    rotation_angle: float
-    confidence: float
-    inlier_count: int
-    transform: Sim3Transform
-    reprojection_error: float
+from gps_denied.hot_types.alignment_result import (  # noqa: F401
+    AlignmentResult,
+    ChunkAlignmentResult,
+    Sim3Transform,
+)
 
 
 class LiteSAMConfig(BaseModel):
@@ -51,3 +22,11 @@ class LiteSAMConfig(BaseModel):
     max_reprojection_error: float = 2.0  # pixels
     multi_scale_levels: int = 3
     chunk_min_inliers: int = 30
+
+
+__all__ = [
+    "AlignmentResult",
+    "ChunkAlignmentResult",
+    "LiteSAMConfig",
+    "Sim3Transform",
+]