Intelligent active fault-tolerant system for multi-source integrated navigation system based on deep neural network

This paper proposes an intelligent active fault-tolerant system based on deep neural network. That is, an active fault-tolerant integrated navigation system is established by adding neural network to the fault-tolerant integrated navigation system based on one-class support vector machine fault detection algorithm. When there is no fault, the neural network trains each sub-filter; when there is a fault, the neural network which has been in the training state will predict the fault time data and use the neural network prediction data to replace the fault data into the main filter for fusion. It can be seen from the simulation analysis that the system can detect the fault of the navigation sub-filtering system well, and when the fault occurs, the prediction data of the neural network is used for information fusion. Simulation results show that the system can provide stable and reliable navigation under the condition of time-varying system and observation noise and complex environment.

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