An Off-Axis Flight Vision Display System Design Using Machine Learning
An Off-Axis Flight Vision Display System Design Using Machine Learning
复制标题
使用机器学习的离轴飞行视觉显示系统设计
DOI：
10.1109/jphot.2022.3155250
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发表时间：
2022-04-01
影响因子：
2.4
通讯作者：
Zhao, Jianlin
中科院分区：
文献类型：
--
作者：
Mao, Shan;Ren, Zhenbo;Zhao, Jianlin
提出了一种基于自由曲面的离轴飞行视觉显示系统设计方案，利用机器学习的方法模拟飞行员在起降训练过程中的视距变化。这一设计是通过使用ZEMAX软件进行光线跟踪来实现的，在该软件中，我们构建并优化了一系列满足相应光学规格的初始系统。使用深度神经网络对回归模型进行训练，该回归模型专门用于预测系统自由曲面的拟合多项式模型。我们的结果表明，飞行视觉显示系统的设计可以转化为一个机器学习问题，并通过大量数据的训练和学习来进一步优化，为设计功能更强大、更复杂的成像光学系统提供了一条途径。
We propose an off-axis flight vision display system design with a free-form surface using machine learning to simulate the visual distance variation during take-off and landing training for pilots. This design is realized by ray tracing using ZEMAX software, where we build and optimize a series of initial systems that meet the corresponding optical specifications. A deep neural network is used to train the regression model, which is specifically designed to predict the fitted polynomial model for the free-form surface of the system. Our results demonstrate that the design of a flight visual display system can be transformed into a machine learning problem and further optimized by training and learning with abundant data, providing an avenue to design more powerful and complex imaging optical systems.