A low-cost INS/GPS integration methodology based on random forest regression

Expert Systems with Applications

Volumn 40, Issue 11, 2013, Pages 4653-4659

  Adusumilli, Srujana ^a   Bhatt, Deepak ^a   Wang, Hong ^b   Bhattacharya, Prabir ^c   Devabhaktuni, Vijay ^a  

^a UNIVERSITY OF TOLEDO   (United States)

^b MEDICAL COLLEGE OF OHIO   (United States)

^c 705 Engineering Research Center   (United States)

Author keywords

Artificial Neural Network; Global Positioning System; Inertial Navigation System; Random forest regression

Indexed keywords

COMPUTATIONAL LOADS; FUSION TECHNIQUES; GENERALIZATION CAPABILITY; INERTIAL NAVIGATION SYSTEMS (INS); INS/GPS INTEGRATION; NAVIGATION SOLUTION; POSITIONAL ERRORS; RANDOM FORESTS;

DECISION TREES; GLOBAL POSITIONING SYSTEM; NEURAL NETWORKS; REGRESSION ANALYSIS; TRACKING (POSITION);

INERTIAL NAVIGATION SYSTEMS;

EID: 84876039259     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2013.02.002     Document Type: Article

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