In geomagnetic aided navigation, directional matching suitability can be depicted by the directional features extracted from candidate matching areas. First, Gabor filtering and gray-level co-occurrence matrix are used to extract frequency-domain and spatial-domain directional features, respectively. Meanwhile, the parameter settings of the above methods are also discussed in order to make the extracted features correctly reflect the directional matching suitability. Then, adaptive neuro-fuzzy inference system is utilized for modeling the complementary relationship between Gabor filtering and gray-level co-occurrence matrix with the purpose of playing their respective advantages in directional matching suitability analysis. Afterward, a hierarchical decision-making scheme is designed, where the first stage is to use adaptive neuro-fuzzy inference system for selecting an appropriate analysis method (Gabor filtering or gray-level co-occurrence matrix) based on the characteristics of the given candidate matching area, and the second stage is to utilize the selected method for directional matching suitability analysis. Experimental results show that the proposed scheme is effective, and the conclusions can afford credible guidance for geomagnetic matching.
A hierarchical decision-making scheme for directional matching suitability analysis in geomagnetic aided navigation
2014-08-01
16 pages
Article (Journal)
Electronic Resource
English
SAGE Publications | 2014
|Route Planning of Geomagnetic Aided Navigation for Vehicle under Matching Suitability Constraints
Trans Tech Publications | 2013
|