Deconvolution
Beams with Unsymmetric Loadings
Beams with Symmetric Loadings
Fast Fourier Transform
Maxwell-Boltzmann Distribution: Problem Solving
Linear Approximation in Frequency Domain
您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
Updated: Sep 9, 2025

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
Published on: July 30, 2020
Jianli Huang1, Yu Wang1, Zaixiao Gong1
1State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, Chinahuangjianli@mail.ioa.ac.cn, wy@mail.ioa.ac.cn, gzx@mail.ioa.ac.cn, nhq@mail.ioa.ac.cn, wangj@mail.ioa.ac.cn, whb@mail.ioa.ac.cn.
这项研究引入了离网稀疏贝叶斯式学习,用于解卷束形成,增强现实目标的空间分辨率. 改进的方法克服了传统技术的转移变量束图案的局限性,并针对采样网.
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: