相关实验视频
Updated: Jan 8, 2026

10:09
Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
7.0K
概括
这项研究引入了一种新的混合追踪方法,使用长短期记忆 (LSTM) 神经网络进行卫星激光通信. 该方法通过预测终端指向来增强指向,获取和跟踪 (PAT) 系统的稳定性和动态响应.
科学领域:
- 光学工程的光学工程.
- 航空航天工程是航空航天工程.
- 人工智能的人工智能是人工智能.
背景情况:
- 稳定的光束跟踪对于可靠的卫星激光通信至关重要.
- 指标,获取和跟踪 (PAT) 系统面临外部干扰和系统延迟带来的挑战.
- 现有的粗跟踪系统具有较低的动态响应,并引入级联延迟.
研究的目的:
- 提出一种混合追踪方法,以提高PAT系统的性能.
- 为了解决卫星激光通信中的动态响应,信号检测延迟和控制滞后的局限性.
- 为了提高光学天线在动态环境中的稳定性和跟踪精度.
主要方法:
- 实施了使用长短期记忆 (LSTM) 神经网络进行终端指向预测的混合追踪方法.
- 集成的基于LSTM的指向预测与单探测器闭环跟踪.
- 利用历史指向轨迹进行短期终端指向预测.
主要成果:
- 提出的基于LSTM的方法提高了PAT系统的动态跟踪能力和强大的稳定性.
- 该方法不受轨道预测错误和卫星态度控制错误的影响,避免了额外的系统错误.
- 模拟和实验证实了混合追踪方法的有效性.
结论:
- 混合追踪方法显著提高了 PAT 系统在卫星激光通信中的性能.
- 基于LSTM的指向预测为终端跟踪提供了对短暂预测的强大替代方案.
- 综合方法导致在太空中更可靠,更稳定的光学链接.
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