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 twocomponent 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 nonstationary thermal fields.

Keywords: neural network, navigation system, time model of the sensors errors, errors interconnection function, unobservation, model adequacy, verification, neural network algorithm, increasing the accuracy

ACM Classification Keywords: I.5.1 Models - Neural nets

Link:

INTELLIGENCE ALGORITHMS FOR INCREASING NAVIGATION SYSTEMS ACCURACY

Aleksandr Zbrutsky, Mohamed Rahmouni

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p08.pdf