A Fuzzy Pattern Based ICCP Matching Algorithm in Gravity-Aided Navigation

The gravity anomalies data has been introduced as a supplementary information to the Inertial Navigation Systems (INSs) to limit its inherent errors accumulated over time. The article mainly focuses on the improvement of iterative closest contour point(ICCP) algorithm commonly used in the gravity-aided inertial navigation system(GAINS). Dealing with the noise of gravimeter measurement data, the algorithm is generalized in the aspect of the accuracy and robustness by a kind of fuzzy pattern recognition technique which gives each sample point a special weight based on its noise size. To reduce the consumption of data sampling time, a simple point matching strategy is proposed. When the system gets a new point, it would be the last one of the next matching line while the first point of the current matching line would be abandoned. The simulation proves that the generalization of the algorithm could achieve high accuracy and timeliness to meet the requirement of AUVs navigation.