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A Feasibility Study of Machine Learning Based Coarse Alignment
Idan Zak,
Itzik Klein
, Reuven Katz
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peer-review
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Dive into the research topics of 'A Feasibility Study of Machine Learning Based Coarse Alignment'. Together they form a unique fingerprint.
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Keyphrases
Machine Learning Based
100%
Coarse Alignment
100%
Alignment Method
60%
Alignment Process
60%
Inertial Navigation System
40%
Navigation Solution
40%
Random Forest
20%
Machine Learning Approach
20%
Machine Learning
20%
Inertial Sensors
20%
Machine Learning Algorithms
20%
Sensor Readings
20%
Initial Attitude
20%
Solution Accuracy
20%
Boosting Method
20%
Low-cost Inertial Sensors
20%
Accuracy Performance
20%
XGBoost
20%
Roll Angle
20%
Pitch Angle
20%
Learning Results
20%
Accelerometer Readings
20%
Convergence Performance
20%
System Scenarios
20%
Computer Science
Machine Learning
100%
Learning System
100%
Random Decision Forest
50%
Sensor Reading
50%
Machine Learning Algorithm
50%
Machine Learning Approach
50%
Learning Result
50%
Extreme Gradient Boosting
50%
System Scenario
50%
Engineering
Feasibility Study
100%
Learning System
100%
Inertial Navigation System
66%
Inertial Sensor
66%
Learning Approach
33%
Sensor Reading
33%
Machine Learning Algorithm
33%
Pitch Angle
33%
Roll Angle φ
33%
Random Forest
33%