GNSS水汽层析的约束条件方程变权代数重构算法

基于传统代数重构算法（algebraic reconstruction technique, ART）提出一种约束条件方程变权的代数重构算法(variable weight algebraic reconstruction technique, VWART),利用2019-08香港地区CORS网GNSS观测数据进行实验,选用京士柏探空气象站探空数据进行验证分析。结果表明,相比于传统代数重构算法,变权代数重构算法的精度、稳定性和可靠性均有所提高。以探空数据为例,其RMSE降低20.334%;在不同程度降水条件下,变权代数重构算法反演的垂直水汽廓线分布均优于传统代数重构算法。     

基于100 nm砷化镓pHEMT工艺的C波段宽带低噪声放大器芯片

作为射电天文接收机系统的关键器件, 低噪声放大器的噪声和增益性能对接收机系统的灵敏度有重要影响. 采用100nm砷化镓赝配高电子迁移率晶体管(pseudomorphic High Electron Mobility Transistor, pHEMT)\lk工艺, 研制了一款可覆盖C波段(4--8GHz)的低噪声放大器(Low Noise Amplifier, LNA). 所设计的LNA采用3级共源级联放大拓扑结构, 栅极、漏极双电源供电. 常温下测试表明, 该LNA在4--8GHz频段内平均噪声温度为\lk60K, 在5GHz处获得最低噪声温度50K, 通带内增益($31\pm1.5$)dB, 输入输出回波损耗均优于10dB, 芯片面积为$2.1\times1.1$mm², 可以应用于C波段射电天文接收机以及卫星通信系统等.     

Automated Separation of Stars and Normal Galaxies Based on Statistical Mixture Modeling with RBF Neural Networks

For LAMOST, the largest sky survey program in China, the solution of the problem of automatic discrimination of stars from galaxies by spectra has shown that the results of the PSF test can be significantly refined. However, the problem is made worse when the redshifts of galaxies are not available. We present a new automatic method of star/(normal) galaxy separation, which is based on Statistical Mixture Modeling with Radial Basis Function Neural Networks (SMM-RBFNN). This work is a continuation of our previous one, where active and non-active celestial objects were successfully segregated. By combining the method in this paper and the previous one, stars can now be effectively separated from galaxies and AGNs by their spectra-a major goal of LAMOST, and an indispensable step in any automatic spectrum classification system. In our work, the training set includes standard stellar spectra from Jacoby's spectrum library and simulated galaxy spectra of EO, SO, Sa, Sb types with redshift ranging from 0 to 1     

宽波段傅里叶变换太阳光谱仪等光程差采样系统设计

太阳成像光谱探测是诊断太阳大气磁场和热力学参数的主要手段. 傅里叶变换太阳光谱仪(Fourier Transform Solar Spectrometer, FTSS)具有宽波段的优势, 是当前中红外高分辨率太阳光谱探测的最佳选择. FTSS通过采集目标辐射等光程差干涉图, 反演获得光谱图, 等光程差采样的间隔决定了反演光谱波长范围. 因此从FTSS宽波段光谱观测对不同等光程差采样间隔需求出发, 基于现场可编程门阵列(Field Programmable Gate Array, FPGA)技术, 采用全数字分频、倍频方案, 设计了一套宽波段FTSS等光程差采样系统. 采用分布式余数补偿方法, 有效解决了在参考激光干涉信号倍频过程中, 输出采样信号在输出信号周期间误差累积问题, 并降低了输出采样信号的误差及非均匀性; 经功能仿真及实验测试, 系统在200Hz--50kHz频率范围内, 频率误差delta $<$ 0.04%, 可有效满足FTSS的300nm--25μm宽波段的光谱观测数据采集需求, 为后续可见和红外波段FTSS的研制奠定了技术基础.     

Surface images of the short period contact binary AE Phe

We present high resolution Doppler images of the short period (P = 0.362 d) contact binary AE Phe. Using least squares deconvolution, we make use of the information content of the several thousand lines in each échelle spectrum to obtain the necessary S/N and time resolution required to resolve individual starspot features. A single pair of rotationally broadened profiles (free of sidelobes due to blending) with a typical S/N of 3000 ‐ 4000 per spectrum is thus obtained. With 300 sec exposures we achieve a cadence of 350 sec which is equivalent to sampling the rotation phase every 4°. We derive images for four nights of data which reveal starspots at most latitudes on both components of the common envelope system. Individual starspots evolve significantly on very short timescales, of order one day; significantly faster than the week timescales found on active single stars and the Sun. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Optimising optimal image subtraction

Difference imaging is a technique for obtaining precise relative photometry of variable sources in crowded stellar fields and, as such, constitutes a crucial part of the data reduction pipeline in surveys for microlensing events or transiting extrasolar planets. The Optimal Image Subtraction (OIS) algorithm of Alard & Lupton (1998) permits the accurate differencing of images by determining convolution kernels which, when applied to reference images with particularly good seeing and signal‐to‐noise (S/N), provide excellent matches to the point‐spread functions (PSF) in other images of the time series to be analysed. The convolution kernels are built as linear combinations of a set of basis functions, conventionally bivariate Gaussians modulated by polynomials. The kernel parameters, mainly the widths and maximal degrees of the basis function model, must be supplied by the user. Ideally, the parameters should be matched to the PSF, pixel‐sampling, and S/N of the data set or individual images to be analysed. We have studied the dependence of the reduction outcome as a function of the kernel parameters using our new implementation of OIS within the IDL‐based TRIPP package. From the analysis of noise‐free PSF simulations of both single objects and crowded fields, as well as the test images in the ISIS OIS software package, we derive qualitative and quantitative relations between the kernel parameters and the success of the subtraction as a function of the PSF widths and sampling in reference and data images and compare the results to those of other implementations found in the literature. On the basis of these simulations, we provide recommended parameters for data sets with different S/N and sampling. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Foreground separation methods for satellite observations of the cosmic microwave background

A maximum entropy method (MEM) is presented for separating the emission resulting from different foreground components from simulated satellite observations of the cosmic microwave background radiation (CMBR). In particular, the method is applied to simulated observations by the proposed Planck Surveyor satellite. The simulations, performed by Bouchet &38; Gispert, include emission from the CMBR and the kinetic and thermal Sunyaev–Zel'dovich (SZ) effects from galaxy clusters, as well as Galactic dust, free–free and synchrotron emission. We find that the MEM technique performs well and produces faithful reconstructions of the main input components. The method is also compared with traditional Wiener filtering and is shown to produce consistently better results, particularly in the recovery of the thermal SZ effect.