Determination of land surface temperature using precipitable water based Split-Window and Artificial Neural Network in Turkey

Land surface temperature (LST) calculation utilizing satellite thermal images is very difficult due to the great temporal variance of atmospheric water vapor in the atmosphere which strongly affects the thermal radiance incoming to satellite sensors. In this study, Split-Window (SW) and Radial Basis Function (RBF) methods were utilized for prediction of LST using precipitable water for Turkey. Coll 94 Split-Window algorithm was modified using regional precipitable water values estimated from upper-air Radiosond observations for the years 1990–2007 and Local Split-Window (LSW) algorithms were generated for the study area. Using local algorithms and Advanced Very High Resolution Radiometer (AVHRR) data, monthly mean daily sum LST values were calculated. In RBF method latitude, longitude, altitude, surface emissivity, sun shine duration and precipitable water values were used as input variables of the structure. Correlation coefficients between estimated and measured LST values were obtained as 99.23% (for RBF) and 94.48% (for LSW) at 00:00 UTC and 92.77% (for RBF) and 89.98% (for LSW) at 12:00 UTC. These meaningful statistical results suggest that RBF and LSW methods could be used for LST calculation.     

一种基于Kalman滤波的卫星遥测数据判读系统

分析了卫星遥测数据的变化规律,提出了一种基于卡尔曼(Kalman)滤波的遥测数据判读系统框架,并定义了系统中各模块的功能及接口关系,应用卫星实际遥测数据对判读系统的数据预测效果进行了验证。结果表明,此系统对数据异常反应迅速,能够很好地满足卫星测试的实时性要求。     

Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall

In the present paper, an artificial neural network (ANN) based technique has been developed to estimate instantaneous rainfall by using brightness temperature from the IR sensors of SEVIRI radiometer, onboard Meteosat Second Generation (MSG) satellite. The study is carried out over north of Algeria. For estimation of rainfall, weight matrices of two ANNs namely MLP1 and MLP2 are developed. MLP1 is to identify raining or non-raining pixels. When rainy pixels are identified, then for those pixels, instantaneous rainfall is estimated by using MLP2. For identification of raining and non raining pixels, 7 input parameters from the IR sensors are utilized. Corresponding data of raining/non-raining pixels are taken from radar. For instantaneous rainfall estimation, 14 input parameters are utilized, where 7 parameters are information about raining pixels and 7 parameters are related with cloud features. The results obtained show the neural network performs reasonably well.     

Spectroscopic data and Stark broadening of Cu I and Ag I spectral lines: Selection and analysis

Optical emission and linear laser absorption spectroscopy techniques were used in investigation of plasma with copper and silver admixture. The method of selection of spectral lines and spectroscopic data with the aim of diagnostics of multicomponent air plasma with two metal vapors admixture was developed. Energy level populations behavior on the Boltzmann plot were used for Cu I and Ag I spectroscopic data selection. In this way the selection of spectroscopic data for some of Cu I and Ag I lines was realized. Stark broadening parameters of Cu I and Ag I were examined. Experimentally obtained temperature and electron density radial distributions were used in the calculation of plasma composition in the assumption of local thermodynamic equilibrium. Linear laser absorption spectroscopy was used to examine the state of plasma.     

Lagrangian analysis of satellite-derived currents: Application to the North Western Mediterranean coastal dynamics

Optimal interpolation methods for improving the reconstruction of coastal dynamics from along-track satellite altimetry measurements have been recently developed over the North Western Mediterranean Sea. Maps of satellite-derived geostrophic current anomalies are generated using these methods, and added to different mean circulation fields in order to obtained absolute geostrophic currents. The resulting fields are then compared to standard AVISO products, and their accuracies are assessed with Lagrangian diagnostics. The trajectories of virtual particle clusters are simulated with a Lagrangian code either with new current fields or with the AVISO ones. The simulated trajectories are then compared to 16 in situ drifter trajectories to evaluate the performance of the different velocity fields. The comparisons show that the new current fields lead to better results than the AVISO one, especially over the shallow continental shelf of the Gulf of Lion. However, despite the use of innovative strategies, some altimetry limitations still persist in the coastal domain, where small scale processes remain sub-sampled by conventional altimetry coverage but will benefit from technological development in the near future. Some of the limitations of the Lagrangian diagnostics presently used are also analyzed, but dedicated studies will be required for future further investigations.     

Comprehensive data reduction package for the Immersion GRating INfrared Spectrograph: IGRINS

We present a Python-based data reduction pipeline package (PLP) for the Immersion GRating INfrared Spectrograph (IGRINS), an instrument that covers the complete H- and K-bands in one exposure with a spectral resolving power of 40,000. The reduction steps carried out by the PLP include flat-fielding, background removal, order extraction, distortion correction, wavelength calibration, and telluric correction using spectra of A type standard stars. As the spectrograph has no moving parts, the PLP automatically reduces the data using predefined functions for the processes of order extraction, distortion correction, and wavelength calibration. Before the telluric correction of the target spectra, the intrinsic hydrogen absorption features of the standard A star are removed with a Gaussian fitting algorithm. The final result is the flux of the target as a function of wavelength. Users can customize the predefined functions for the extraction of the spectrum from the echellogram and adjust the parameters for the fitting functions for the spectra of celestial objects, using “fine-tuning” options, as necessary. Presently, the PLP produces the best results for point-source targets.     

The effect of spatial truncation error on variance of gravity anomalies derived from inversion of satellite orbital and gradiometric data

The spatial truncation error (STE) is a significant systematic error in the integral inversion of satellite gradiometric and orbital data to gravity anomalies at sea level. In order to reduce the effect of STE, a larger area than the desired one is considered in the inversion process, but the anomalies located in its central part are selected as the final results. The STE influences the variance of the results as well because the residual vector, which is contaminated with STE, is used for its estimation. The situation is even more complicated in variance component estimation because of its iterative nature. In this paper, we present a strategy to reduce the effect of STE on the a posteriori   variance factor and the variance components for inversion of satellite orbital and gradiometric data to gravity anomalies at sea level. The idea is to define two windowing matrices for reducing this error from the estimated residuals and anomalies. Our simulation studies over Fennoscandia show that the differences between the 0.5°×0.5°$0.5°\times 0.5°$ gravity anomalies obtained from orbital data and an existing gravity model have standard deviation (STD) and root mean squared error (RMSE) of 10.9 and 12.1 mGal, respectively, and those obtained from gradiometric data have 7.9 and 10.1 in the same units. In the case that they are combined using windowed variance components the STD and RMSE become 6.1 and 8.4 mGal. Also, the mean value of the estimated RMSE after using the windowed variances is in agreement with the RMSE of the differences between the estimated anomalies and those obtained from the gravity model.     

基于图像的经纬仪测量目标快速瞄准技术

电子经纬仪是一种高精度的测角仪器,由多台高精度电子经纬仪构成的测量系统可以实现三维坐标测量,用于对大型工业产品的几何检测。但经纬仪在测量过程中仍然需要人工瞄准目标,存在速度慢、效率低、人为因素影响大等不足。实现经纬仪自动照准目标功能将是一个新的发展方向。提出一种基于图像的自动瞄准技术,通过在经纬仪上安装一台相机获取待测目标点的图像,利用图形目标识别技术获取目标点图像坐标,依据相机与经纬仪的空间关系可以获得各目标点相对于经纬仪的初始角度,从而实现目标点的快速概略定位,理论推导及实验证明本方法能够准确有效的获得目标点的概略位置。     

四轴飞行器姿态监控系统设计

设计了一套四轴飞行器上位机监控系统。针对准确掌握四轴飞行器的实时姿态、位置等信息和对四轴飞行器进行精准控制两大核心问题,开发了由上位机实现四轴飞行器姿态数据采集、通信及控制等功能的监控系统。监控系统良好的功能设计和友好的人机界面使得用户能够准确掌握飞行器的飞行信息,从而能够更精准地控制四轴飞行器飞行姿态。实验验证,监控系统简单实用,性能稳定,精度高,使整个飞行系统抗干扰能力强,鲁棒性、稳定性好。     

风切变场中直升机前飞状态动态响应

为解决复杂风切变场中直升机运动的数值仿真,把握非线性直升机模型在风场中的响应特性,建立了一维、二维的风切变模型,采用直升机非线性飞行动力学模型,考虑直升机的控制系统,用四阶龙格－库塔法数值仿真直升机在风场中的前飞运动.对水平风和铅垂风的各个梯度场对响应的影响进行比较.结果表明,水平风和铅垂风的各个梯度场对响应的影响是不同的,此研究中二维空间的组合梯度场构成更为危险的飞行环境;在不同的情况下其作用是不可忽略的,尤其注意在低空飞行状态下对直升机飞行性能的影响.也进一步说明此数值仿真法对非线性直升机模型在复杂风场中响应研究实用有效.