feat(eskf): add ESKF schema contracts (ESKF-01, ESKF-04, ESKF-05)

ConfidenceTier, IMUMeasurement, ESKFConfig, ESKFState Pydantic models.
Re-exported from schemas/__init__.py.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/gps_denied/schemas/__init__.py

@@ -37,3 +37,6 @@ class Geofences(BaseModel):
     """Collection of geofence polygons."""
 
     polygons: list[Polygon] = Field(default_factory=list)
+
+
+from gps_denied.schemas.eskf import ConfidenceTier, ESKFConfig, ESKFState, IMUMeasurement  # noqa: E402

src/gps_denied/schemas/eskf.py

@@ -0,0 +1,68 @@
+"""Error-State Kalman Filter schemas."""
+
+from enum import Enum
+from typing import Optional
+
+import numpy as np
+from pydantic import BaseModel, Field
+
+
+class ConfidenceTier(str, Enum):
+    """ESKF confidence tier for GPS_INPUT fix_type mapping."""
+    HIGH = "HIGH"       # Satellite match <30s ago, covariance < 400 m^2
+    MEDIUM = "MEDIUM"   # VO tracking OK, no recent satellite match
+    LOW = "LOW"         # IMU-only, cuVSLAM lost
+    FAILED = "FAILED"   # 3+ consecutive total failures
+
+
+class IMUMeasurement(BaseModel):
+    """Single IMU reading from flight controller."""
+    model_config = {"arbitrary_types_allowed": True}
+
+    accel: np.ndarray  # (3,) m/s^2 in body frame
+    gyro: np.ndarray   # (3,) rad/s in body frame
+    timestamp: float   # seconds since epoch
+
+
+class ESKFConfig(BaseModel):
+    """ESKF tuning parameters."""
+
+    # Process noise (from IMU datasheet — ICM-42688-P)
+    accel_noise_density: float = 6.86e-4   # 70 ug/sqrt(Hz) -> m/s^2/sqrt(Hz)
+    gyro_noise_density: float = 5.24e-5    # 3.0e-3 deg/s/sqrt(Hz) -> rad/s/sqrt(Hz)
+    accel_random_walk: float = 2.0e-3      # m/s^3/sqrt(Hz)
+    gyro_random_walk: float = 8.73e-7      # 5.0e-5 deg/s^2/sqrt(Hz) -> rad/s^2/sqrt(Hz)
+
+    # VO measurement noise
+    vo_position_noise: float = 0.3         # meters (cuVSLAM at 600m altitude)
+
+    # Satellite measurement noise range
+    sat_noise_min: float = 5.0             # meters (high-confidence RANSAC)
+    sat_noise_max: float = 20.0            # meters (low-confidence RANSAC)
+
+    # Confidence tier thresholds
+    satellite_max_age: float = 30.0        # seconds
+    covariance_high_threshold: float = 400.0  # m^2 (trace of position covariance)
+
+    # Initial covariance diagonals
+    init_pos_var: float = 100.0            # m^2
+    init_vel_var: float = 1.0              # (m/s)^2
+    init_att_var: float = 0.01             # rad^2
+    init_accel_bias_var: float = 0.01      # (m/s^2)^2
+    init_gyro_bias_var: float = 1e-6       # (rad/s)^2
+
+
+class ESKFState(BaseModel):
+    """Full ESKF nominal state snapshot."""
+    model_config = {"arbitrary_types_allowed": True}
+
+    position: np.ndarray       # (3,) ENU meters from origin (East, North, Up)
+    velocity: np.ndarray       # (3,) ENU m/s
+    quaternion: np.ndarray     # (4,) [w, x, y, z] body-to-ENU
+    accel_bias: np.ndarray     # (3,) m/s^2
+    gyro_bias: np.ndarray      # (3,) rad/s
+    covariance: np.ndarray     # (15, 15)
+    timestamp: float           # seconds since epoch
+    confidence: ConfidenceTier
+    last_satellite_time: Optional[float] = None
+    last_vo_time: Optional[float] = None