Accurate absolute position, velocity, attitude and precise relative navigation are critical capabilities for unmanned air vehicles (UAVs) to improve their autonomy and reduce the mission life-cycle cost. This Phase I project investigates a low cost, miniature reconfigurable autonomous navigation system for all flight missions of the UAV. The proposed approach employs a flexible Federated Kalman filtering architecture and an onboard knowledge-based expert system to integrate a MEMS IMU, a multi-antenna GPS receiver, a Wide Area Augmentation System (WAAS) receiver, a data link receiver for DGPS corrections, and a radar altimeter. The configured integrated GPS/MEMS IMU system presents a high degree of navigation performance for UAV?s flight phases, release, cruise, approaching, and landing. The configured multi-antenna GPS interferometer/MEMS IMU integration provides a navigation solution for the UAV?s cruise operations, while the configured GPS/WAAS/MEMS IMU/Radar Altimeter integration provides precise approach and landing capabilities for the UAV. An intelligent neural network is applied to perform multi-sensor failure detection and isolation, and redundancy management. AGNC commercial products and AGNC US patents providing advanced integration technologies for MEMS IMU, GPS, WAAS, and radar altimeter will insure a successful project.