在时间域中反光束形成.
Zvi Aharon Herscovici1, Israel Cohen1
1Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering, Technion-Israel Institute of Technology, Haifa 3200003, Israel.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
这项研究引入了一种新的时间域反光束转换器,用于准确的实时源定位,通过改善到达方向和信号范围估计,提高自动化和人工智能,即使信号噪声比率低.
科学领域:
- 信号处理 信号处理
- 声学 声学 在声学上
- 人工智能的人工智能
背景情况:
- 实时源本地化对于先进的自动化和AI应用程序至关重要.
- 低信号噪声比 (SNR) 和处理时间限制挑战了定位准确性.
- 现有的方法可能无法满足高端系统的苛刻要求.
研究的目的:
- 为实时源定位提出一个新的基于时间域反的光束转换器架构.
- 为了估计反射源的到达方向 (DOA) 和信号范围.
- 通过集成的反机制来提高定位精度.
主要方法:
- 开发一种基于时间域反的新型光束转换器架构.
- 对反射源的到达方向 (DOA) 和信号范围的估计.
- 对拟议方法与传统时间域技术进行比较分析.
主要成果:
- 拟议的架构有效地解决了实时处理需求.
- 反机制显著提高了定位精度.
- 使用峰值与侧叶比率,主叶宽度和导向因子的性能评估显示,光束变频器的有效性得到了改善.
结论:
- 开发的时间域反束变频器为实时应用程序的定位精度提供了显著的改进.
- 这种方法通过克服SNR和处理时间限制来提高自动化和AI系统的性能.
- 反集成是光束成型的关键进步,用于精确定位源.
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