摘要翻译：
本文研究射电天文学中传感器阵列的标定问题。当前和未来的射电望远镜需要高效的算法来克服大采集面积、宽视场和大数据量的新技术挑战。具体来说，我们研究了具有显著方向相关畸变的无线电干涉测站的校准。本文提出了一种基于松弛的最大似然估计器的迭代鲁棒校准算法，该算法适用于特定的环境：（1）观测数据受异常值的影响，以及（2）感兴趣的参数具有特定的依赖于频率的结构。参数跨频率的变化通过分布式过程来解决，这与新的无线电合成阵列在整个观测带宽被划分为多个频率信道的情况是一致的。数值仿真表明，所提出的鲁棒分布式校准估计器优于传统的非鲁棒算法和/或单频情况。
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英文标题：
《Robust Calibration of Radio Interferometers in Multi-Frequency Scenario》
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作者：
Virginie Ollier, Mohammed Nabil El Korso, Andr\'e Ferrari, R\'emy
  Boyer, Pascal Larzabal
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最新提交年份：
2018
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Physics        物理学
二级分类：Instrumentation and Methods for Astrophysics        天体物理学仪器和方法
分类描述：Detector and telescope design, experiment proposals. Laboratory Astrophysics. Methods for data analysis, statistical methods. Software, database design
探测器和望远镜设计，实验建议。实验室天体物理学。资料分析方法，统计方法。软件，数据库设计
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  This paper investigates calibration of sensor arrays in the radio astronomy context. Current and future radio telescopes require computationally efficient algorithms to overcome the new technical challenges as large collecting area, wide field of view and huge data volume. Specifically, we study the calibration of radio interferometry stations with significant direction dependent distortions. We propose an iterative robust calibration algorithm based on a relaxed maximum likelihood estimator for a specific context: i) observations are affected by the presence of outliers and ii) parameters of interest have a specific structure depending on frequency. Variation of parameters across frequency is addressed through a distributed procedure, which is consistent with the new radio synthesis arrays where the full observing bandwidth is divided into multiple frequency channels. Numerical simulations reveal that the proposed robust distributed calibration estimator outperforms the conventional non-robust algorithm and/or the mono-frequency case.
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PDF链接：
https://arxiv.org/pdf/1807.11314