---
plan: 01-01
phase: 01-eskf-core
status: complete
started: 2026-04-01T20:36:07Z
completed: 2026-04-01T20:45:00Z
---

## Summary

Implemented the 15-state Error-State Kalman Filter (ESKF) from scratch using NumPy only. Covers ESKF-01 through ESKF-05.

## Key Files Created

- `src/gps_denied/schemas/eskf.py` (68 lines) — ConfidenceTier, IMUMeasurement, ESKFConfig, ESKFState schemas
- `src/gps_denied/core/eskf.py` (359 lines) — ESKF class with predict(), update_vo(), update_satellite(), get_confidence(), initialize_from_gps()

## Commits

- `57c7a6b` feat(eskf): add ESKF schema contracts (ESKF-01, ESKF-04, ESKF-05)
- `9d5337a` feat(eskf): implement 15-state ESKF core algorithm (ESKF-01..05)

## Tasks Completed

| Task | Status | Notes |
|------|--------|-------|
| Task 1: ESKF schema contracts | ✓ | All 4 classes importable |
| Task 2: ESKF core algorithm | ✓ | All acceptance criteria passed |

## Deviations

None — implemented as specified in plan.

## Self-Check: PASSED

- [x] ESKF class importable
- [x] predict() propagates state and grows covariance
- [x] update_vo() reduces position uncertainty via Kalman gain
- [x] update_satellite() corrects absolute position
- [x] get_confidence() returns correct tier
- [x] initialize_from_gps() uses CoordinateTransformer
- [x] All math NumPy only, no external filter library