A Statistical Framework for False-Fix Elimination in TERCOM Using Real Flight Test Data

In Terrain Contour Matching (TERCOM), false-fix errors are a significant problem because inaccurate location estimates can lead to catastrophic outcomes. This study presents a statistical methodology for detecting and eliminating false fixes without changing the fundamental TERCOM logic. Six similarity metrics were investigated using 780 synthetic trajectories derived from Flight Test Instrumentation (FTI) data obtained from the Hürjet advanced jet trainer. The most successful outcomes were achieved via mean absolute difference (MAD) and dynamic time warping (DTW). After investigating forty-five features generated from trajectory, terrain, and map-based, the most reliable indicator is determined as the minima ratio, which quantifies the ratio between the two strongest score-map minima. Other reliable indicators were trajectory roughness and roughness difference. Using these indicators, an elimination strategy is conducted and this strategy reduced more than 44% of false fixes while preserving navigation accuracy.