快速射电暴(Fast Radio Burst,FRB)的起源及周边磁环境特性,长期以来是天体物理学界的研究热点与核心谜题,而法拉第旋转量(Rotation Measure,RM)作为探测射电波传播路径上磁场与电子密度分布的关键物理量,其变化特征是破解这一谜题的重...快速射电暴(Fast Radio Burst,FRB)的起源及周边磁环境特性,长期以来是天体物理学界的研究热点与核心谜题,而法拉第旋转量(Rotation Measure,RM)作为探测射电波传播路径上磁场与电子密度分布的关键物理量,其变化特征是破解这一谜题的重要突破口.展开更多
利用毫米波射电天文所(Institut de Radioastronomie Millimétrique,IRAM)30 m射电望远镜在1.3–4.0 mm波段的分子谱线成图,结合70–870μm连续谱数据以及绿岸射电望远镜(Green Bank Telescope,GBT)对NH_(3)(J,K)=(1,1)和(2,2)谱...利用毫米波射电天文所(Institut de Radioastronomie Millimétrique,IRAM)30 m射电望远镜在1.3–4.0 mm波段的分子谱线成图,结合70–870μm连续谱数据以及绿岸射电望远镜(Green Bank Telescope,GBT)对NH_(3)(J,K)=(1,1)和(2,2)谱线的成图(J为总角动量量子数,而K描述角动量在分子主轴方向的分量),对G 011.0970-0.1093纤维状分子云末端的一对比邻云团进行了观测.尽管在870μm波段下它们都表现出与连续谱流量峰值成协,但在70μm波段下,它们呈现出明亮与暗弱的对照特性.对这两个云团进行对比分析发现:(1)该极早期大质量恒星形成区的气体尘埃温度高度耦合;(2)70μm明亮云团的气体尘埃温度从中心(约17 K)到包层边缘呈递减趋势,这预示着云团内部可能已经有原恒星形成;70μm暗弱云团中心较边缘更冷(约11K)更致密(约5×10^(22)cm^(-2)),且氢分子柱密度与尘埃温度存在强反相关,故外部辐射可能主导该云团加热;(3)在pc尺度上,气态C^(18)O的耗损率f_(D)(C^(18)O)与HCO^(+)的氘化率存在强正相关,且气态C^(18)O在冷且致密的DCO^(+)主导云团耗损f_(D)(C^(18)O)高达7;(4)在气体尘埃温度从10 K到20 K,氢分子柱密度从10^(22)cm^(-2)到10^(23)cm^(-2)的变化环境里,HCO^(+)、N_(2)H^(+)、HNC在更.为致密冷暗的环境氘化率增丰明显,HCN则在稍温暖且70μm明亮的环境氘化率增丰更大,而NH3氘化率在此环境中没有明显变化.这些不同分子氘化增丰的差异性可能源自其气体尘埃反应路径的差异性.展开更多
无线电频率占用度是表征无线电频谱真实占用状况的主要指标。针对目前国家规范测量无线电频率占用度以及频率占用度与无线信道状态关联研究存在的问题,建立了无线电信号发射与频谱接收系统,研究了无线电频率占用度测量方法与信道噪声模...无线电频率占用度是表征无线电频谱真实占用状况的主要指标。针对目前国家规范测量无线电频率占用度以及频率占用度与无线信道状态关联研究存在的问题,建立了无线电信号发射与频谱接收系统,研究了无线电频率占用度测量方法与信道噪声模型的关系。实验结果表明,如果信道是高斯噪声信道,可采用国标法进行频率占用度测量;如果信道是非高斯噪声信道,采用5西格玛原则统计频率占用度更好。采用机器学习方法研究了无线信道占用状况,结果表明,信噪比(Signal to Noise Ratio,SNR)大于15 dB时,基于信号频谱分类模型的5类无线电信号的分类准确率可达到99%以上;在低SNR和非高斯噪声信道下如何进一步提高无线电信号的分类准确率是一个挑战。展开更多
针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度...针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度学习等方面研究了射频干扰的预防策略和抑制方法。详细分析了主动预防阶段可采取的方法,预相关阶段的自适应滤波和空间滤波方法,后相关阶段的VarThreshold, SumThreshold和奇异值分解等方法。探讨了基于机器学习的主成分分析、支持向量机、全卷积神经网络、卷积神经网络、U-Net等相关技术和方法在射频干扰信号处理方面的应用。展开更多
Library for Baseband (lbb)是一个自研的用于读取解析甚长基线干涉测量(Very Long Baseline Interferometry, VLBI)基带数据的工具库,主要用于VLBI观测中对终端基带数据的读取、解析及输出结果分析.该软件库通过对基带数据的自动判断,...Library for Baseband (lbb)是一个自研的用于读取解析甚长基线干涉测量(Very Long Baseline Interferometry, VLBI)基带数据的工具库,主要用于VLBI观测中对终端基带数据的读取、解析及输出结果分析.该软件库通过对基带数据的自动判断,自动实现读取不同数据格式的功能,并提供了各种各样的API (Application Programming Interface)功能供用户调用.目前lbb软件库已经成功应用在了探月工程VLBI测轨任务中的硬件相关处理机配置项和测地VLBI观测数据的预处理.文章详细介绍了lbb软件库的设计、功能及用法.展开更多
To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to e...To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.展开更多
Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse p...Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse problem.Reconstructing dirty images into clean ones is crucial for subsequent scientific analysis.To address these challenges,we propose a U-Net based method that extracts high-level information from the dirty image and reconstructs a clean image by effectively reducing artifacts and sidelobes.The U-Net architecture,consisting of an encoder-decoder structure and skip connections,facilitates the flow of information and preserves spatial details.Using simulated data of radio galaxies,we train our model and evaluate its performance on the testing set.Compared with the CLEAN method and the visibility and image conditioned denoising diffusion probabilistic model,our proposed model can effectively reconstruct both extended sources and faint point sources with higher values in the structural similarity index measure and the peak signal-to-noise ratio.Furthermore,we investigate the impact of noise on the model performance,demonstrating its robustness under varying noise levels.展开更多
文摘无线电频率占用度是表征无线电频谱真实占用状况的主要指标。针对目前国家规范测量无线电频率占用度以及频率占用度与无线信道状态关联研究存在的问题,建立了无线电信号发射与频谱接收系统,研究了无线电频率占用度测量方法与信道噪声模型的关系。实验结果表明,如果信道是高斯噪声信道,可采用国标法进行频率占用度测量;如果信道是非高斯噪声信道,采用5西格玛原则统计频率占用度更好。采用机器学习方法研究了无线信道占用状况,结果表明,信噪比(Signal to Noise Ratio,SNR)大于15 dB时,基于信号频谱分类模型的5类无线电信号的分类准确率可达到99%以上;在低SNR和非高斯噪声信道下如何进一步提高无线电信号的分类准确率是一个挑战。
文摘针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度学习等方面研究了射频干扰的预防策略和抑制方法。详细分析了主动预防阶段可采取的方法,预相关阶段的自适应滤波和空间滤波方法,后相关阶段的VarThreshold, SumThreshold和奇异值分解等方法。探讨了基于机器学习的主成分分析、支持向量机、全卷积神经网络、卷积神经网络、U-Net等相关技术和方法在射频干扰信号处理方面的应用。
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077)+5 种基金the Chinese Academy of Sciences(CAS)“Light of West China”Program(No.xbzg-zdsys-202410)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.
基金supported by the National SKA Program of China(2020SKA0110300,2020SKA0110201)the National Natural Science Foundation of China(NSFC,grant Nos.12433012 and 12373097)+1 种基金the Guangdong Province Project of the Basic and Applied Basic Research Foundation(2024A1515011503)the Guangzhou Science and Technology Funds(2023A03J0016).
文摘Deconvolution in radio interferometry faces challenges due to incomplete sampling of the visibilities in the spatial frequency domain caused by a limited number of antenna baselines,resulting in an ill-posed inverse problem.Reconstructing dirty images into clean ones is crucial for subsequent scientific analysis.To address these challenges,we propose a U-Net based method that extracts high-level information from the dirty image and reconstructs a clean image by effectively reducing artifacts and sidelobes.The U-Net architecture,consisting of an encoder-decoder structure and skip connections,facilitates the flow of information and preserves spatial details.Using simulated data of radio galaxies,we train our model and evaluate its performance on the testing set.Compared with the CLEAN method and the visibility and image conditioned denoising diffusion probabilistic model,our proposed model can effectively reconstruct both extended sources and faint point sources with higher values in the structural similarity index measure and the peak signal-to-noise ratio.Furthermore,we investigate the impact of noise on the model performance,demonstrating its robustness under varying noise levels.
