A Novel Recurrent Convolutional Neural Network-Based Estimation Method for Switching Guidance Law

A Novel Recurrent Convolutional Neural Network-Based Estimation Method for Switching Guidance Law

This paper presents a recurrent convolutional neural network-based estimation method of guidance parameters of the pursuer under augmented proportional navigation (APN) guidance law with a time-varying switching navigation ratio. For the highly maneuvering pursuit-evasion process, realistic factors...

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Bibliographic Details
Main Authors: Huibing Shao, Yepeng Han, Changzhu Wei, Ruiming Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Guidance law estimation
pursuit-evasion process
recurrent convolutional neural network
switching navigation ratio
time dependency
Online Access:https://ieeexplore.ieee.org/document/8950354/

Internet

https://ieeexplore.ieee.org/document/8950354/

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