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14 December 2015 Research on matching area selection criteria for gravity gradient navigation based on principal component analysis and analytic hierarchy process
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Proceedings Volume 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 981519 (2015) https://doi.org/10.1117/12.2204819
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
The matching area selection is the foundation of gravity gradient aided navigation. In this paper, a gravity gradient matching area selection criterion is proposed, based on the principal component analysis (PCA) and analytic hierarchy process (AHP). Firstly, the features of gravity gradient are extracted and nine gravity gradient characteristic parameters are obtained. Secondly, combining PCA with AHP, a PA model is built and the nine characteristic parameters are fused based on it. At last, the gravity gradient matching area selection criterion is given. By using this criterion, gravity gradient area can be divided into matching area and non-matching area. The simulation results show that gravity gradient position effect in the selected matching area is superior to the matching area, and the matching rate is greater than 90%, the position error is less than a gravity gradient grid.
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Ling Xiong, Kaihan Li, Jianqiao Tang, and Jie Ma "Research on matching area selection criteria for gravity gradient navigation based on principal component analysis and analytic hierarchy process", Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 981519 (14 December 2015); https://doi.org/10.1117/12.2204819
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