This paper presents a localization system designed to support commercial airliners during PBN CAT I approaches in environments where GNSS signals are degraded or unavailable. The proposed system integrates a vision-based sensor that detects and tracks the runway during the final segment of the approach, providing critical line-of-sight information. This sensor is combined with a high-precision, navigation-grade Inertial Measurement Unit with angular drift on the order of 0.01°/h, a barometric altimeter, and a GNSS receiver. Sensor fusion is performed using an Error-State Kalman Filter (ES-KF) operating in a semi-closed loop architecture. The paper outlines the main steps of the estimation process and evaluates the system’s accuracy against aviation standards. Performance is quantified through figures of merit, defined as 95% confidence bounds, and analyzed across various operational scenarios. Results show that the system consistently meets PBN CAT I accuracy requirements when GNSS remains available up to the final approach segment. In scenarios involving prolonged GNSS outages (coasting phases), vision-based corrections reduce estimation drift, but may not always ensure compliance with the required accuracy thresholds. Nonetheless, the addition of vision significantly improves robustness, highlighting its value in enhancing aircraft navigation resilience.