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.     

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.     

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。     

基于多源卫星融合资料的中国近海海洋锋检测研究

海洋锋是海洋动力学中重要的研究对象.目前主要利用卫星遥感海面温度数据分析海洋锋.由于夏季中国近海海域海面温度趋同特性,无法利用海面温度数据分析海洋锋,而卫星遥感海色数据可以有效弥补海面温度检测海洋锋的不足,提高海洋锋检测的准确性.基于多源卫星融合数据,利用梯度检测算法对中国近海海域进行海洋锋研究,结合海面温度和蓝绿波段...     

城市道路交通流检测数据精度评价

目前各种检测方法采集到的路段速度数据普遍存在一定的误差,其准确性直接影响各种交通分析模型结果的精度.针对浮动车检测器、微波检测器以及线圈检测器的路段速度数据进行研究,利用GPS(Global Positioning System)设备实时记录试验车位置,分别在快速路和主干路进行了12次实验,对不同采集方式获取的速度信息进行了精度验证和评价.实验结果分析表明,浮动车数据获取的城市快速路和主干路的路段行程速度平均误差分别为13.6%和27.8%,且采集值与实际速度具有相同的分布.快速路微波检测器和主干路线圈检测器的速度数据与真实行程速度数据的误差分别为30%和56%.表明了微波检测器的断面速度值,用来表征所处路段的行程速度时虽然具有一定的误差,但是基本能表征路段的行驶状况.该研究结论为不同精度需求的交通模型选择合适的数据源提供支持,并为利用多源数据的冗余信息提高数据精度和完备性提供了理论依据.      

面向IMA网络文件系统的双服务器结构设计

为了提高面向IMA网络文件系统的可靠性和实时性,设计了一种双服务器结构的网络文件系统。客户优先访问主服务器,在得不到主服务器响应时,访问从服务器;主服务器在无法满足同时有多个访问请求时,把一部分的访问请求分给从服务器;主服务器和从服务器通过数据实时更新和定时检测更新,保持数据的高度一致。     

Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport

Aerodynamic modeling and parameter estimation from quick accesses recorder (QAR) data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother (EKF-MBF) method for aerodynamic coefficient identification, the radial basis function (RBF) neural network method for aerodynamic modeling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil airplane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.     

基于 GPS 和电子海图的落水人员搜救定位系统

现阶段我国的海上搜救工作仍然采用救生衣方式的被动求救和大面积搜索的模式,搜救效率较低.为了解决了这个问题,本文设计实现了基于全球定位系统(GPS)和电子海图的落水人员搜救定位系统.该系统将 GPS、地理信息系统(GIS)、数据库同步、无线传输技术有机结合,有效保障了落水人员的精确定位,为救援船舶及时追踪落水人员提供了可靠的依据