NDLI: A Combinational Aided Navigation Algorithm Based on Terrain Variance Entropy and ICCP

Content Provider	IEEE Xplore Digital Library
Author	Gannan Yuan Hongwei Zhang Kefei Yuan Fushan Sun
Copyright Year	2012
Abstract	In order to solve problems that the aided navigation system cannot work well in the flat region and Iterated Closest Contour Point(ICCP) algorithm diverges easily when the initial error of Inertial Navigation System (INS) is big, a new combinational algorithm based on terrain variance entropy and ICCP is proposed. In light of the advantages and disadvantages of two algorithms, they can complement each other. Terrain variance entropy algorithm is firstly applied to reducing the initial error of INS, then the best matching position is obtained by ICCP algorithm. The terrain entropy and the standard deviation of water depth are used as the terrain discriminant index. Simulation experiments are carried out in three different areas and result shows that the error of combinational algorithm maintains below 290m and navigation requirement of underwater vehicle can be satisfied.
Starting Page	835
Ending Page	838
File Size	439768
Page Count	4
File Format	PDF
ISBN	9781467313650
DOI	10.1109/CSO.2012.188
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems aided navigation Navigation terrain variance entropy Entropy Classification algorithms Mathematical model combinational algorithm iterated closest contour point Standards Equations terrain entropy
Content Type	Text
Resource Type	Article

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