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Precise navigation is a fundamental problem of aircraft safety approach and landing. However, the existing methods, including rotorcraft-based and fixed-wing-based, cannot meet the requirements of precision approach and landing of civil aircraft in the global position system (GPS)-denied and low visibility. This paper proposes an autonomous approach and landing navigation method whose accuracy is comparable to Inertial/Differential GPS (DGPS) integration. This method integrates inertial data, forward-looking infrared (FLIR) images, and runway geographic information to estimate kinetics states of aircraft during approach and landing. First, we improve an existing method to robustly detect runway, accurately extract three vertexes of runway contour from FLIR images, and synthesize the virtual runway features by runway geo-information and aircraft’s pose parameters. Second, we propose to use real and synthetic runway features to create vision cues and integrate them with inertial data in square-root unscented Kalman filter to estimate the motion errors. Meanwhile, the measured motion states are corrected with the estimated state errors. Finally, we design a flight data acquisition platform equipped on a general aircraft and use the real flight data to verify our proposed method. The experimental results demonstrate that the proposed method can run smoothly for civil aircraft precision approach and landing.

Infrared-Based Autonomous Navigation for Civil Aircraft Precision Approach and Landing