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Book 2 Advanced Research in Artificial Intelligence >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1031

Title: Intelligence Algorithms for Increasing Navigation Systems Accuracy
Authors: Zbrutsky, Aleksandr
Rahmouni, Mohamed
Keywords: Neural Network
Navigation System
Time Model of the Sensors Errors
Errors Interconnection Function
Unobservation
Model Adequacy
Verification
Neural Network Algorithm
Increasing the Accuracy
Issue Date: 2008
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.
URI: http://hdl.handle.net/10525/1031
ISSN: 1313-0455
Appears in Collections:Book 2 Advanced Research in Artificial Intelligence

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