Harnessing Sparsity Over the Continuum: Atomic norm minimization for superresolution
Harnessing Sparsity Over the Continuum: Atomic norm minimization for superresolution
复制标题
DOI：
10.1109/msp.2019.2962209
复制
发表时间：
2019-04
影响因子：
14.9
通讯作者：
Yuejie Chi;Maxime Ferreira Da Costa
中科院分区：
文献类型：
--
作者：
Yuejie Chi;Maxime Ferreira Da Costa
在许多传感和成像应用的核心，感兴趣的信号可以被建模为某个模板的平移或调制版本的线性叠加[例如，点扩展函数(PSF)或格林函数]，并且基本问题是从噪声测量中估计平移或调制参数(例如，延迟、位置或多普勒)。这一问题不仅对雷达和声纳中的目标定位、无线通信中的信道估计和阵列信号处理中的到达方向估计，而且对于现代成像手段，如超分辨率单分子荧光显微镜、核磁共振成像和神经记录中的棘波定位等都具有重要意义。
At the core of many sensing and imaging applications, the signal of interest can be modeled as a linear superposition of translated or modulated versions of some template [e.g., a point spread function (PSF) or a Green's function] and the fundamental problem is to estimate the translation or modulation parameters (e.g., delays, locations, or Dopplers) from noisy measurements. This problem is centrally important to not only target localization in radar and sonar, channel estimation in wireless communications, and direction-of-arrival estimation in array signal processing, but also modern imaging modalities such as superresolution single-molecule fluorescence microscopy, nuclear magnetic resonance imaging, and spike localization in neural recordings, among others.