Geomagnetic Matching Navigation for Aircraft Based on Improved Iterative Closest Contour Point Algorithm

Abstract

Focusing on the problem of accumulated INS error of high-speed aircraft at high-altitude with unavailable satellite navigation, an improved iterative closest contour point (ICCP) algorithm is proposed for geomagnetic matching navigation helping eliminate INS errors. Aiming at local optimal problem of traditional ICCP with large initial positioning error, proposed algorithm improves its decision indicator based on multi-attribute decision-making. Matching effect is evaluated comprehensively by algorithm convergence degree indicator together with introduced trajectory correlation indicator. After judging the convergence degree of matching trajectory, its correlation with real trajectory is depicted by their geomagnetic intensity and linear correlation. Then, the fusion of two indicators based on entropy weight method is adopted as comprehensive decision indicator. Improved ICCP is compared with particle swarm optimization algorithm (PSO) to verify its matching effect in conditions of different map resolution and geomagnetic measurement noise. Experiment results indicate that improved algorithm's performance is significantly better than PSO and traditional ICCP with higher matching accuracy and better stability, helping optimize and decrease matching error of ICCP from thousands of meters to 100 meters.