Impact of geomagnetic variation over sub-auroral ionospheric region during high solar activity year 2014

The present work is an attempt to evaluate the impact of changing space weather condition over sub-auroral ionosphere during high solar activity year 2014. In view of this, the GPS based TEC along with Ionosonde data over Indian permanent scientific base “Maitri”, Antarctica (70°46′00″S, 11°43′56″E) has been utilized. The results suggested that the nature of ionospheric responses to the geomagnetic disturbances not only depended upon the status of high latitudinal electro-dynamic processes but also influenced by the seasonal variations. The results revel both negative and positive type of ionospheric response in a single year but during different seasons. The study suggested that the combination of equator-ward plasma transportation along with ionospheric compositional changes causes a negative ionospheric impact especially during summer and equinox seasons. However, the combination of pole-ward contraction of the oval region along with particle precipitation may lead to exhibit positive ionospheric response during the winter season. The plasma transportation direction has been validated with the help of convection boundary (HM boundary) deduced with the help of SuperDARN observations. The ground based ionosonde observations clearly provided the evidence of deep penetration of high energetic particles up to the E-layer heights which results a sudden and strong appearance of E-layer. The strengthening of E-layer is responsible for modification of auroral electrojet and field-aligned current system. Also, the sudden appearance of E-layer along with a decrease in F-layer electron density suggested the dominance of NO⁺ over O⁺ in a considered region under geomagnetic disturbed condition.     

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

调频连续波SAR改进的频率尺度变换算法(英文)

本文提出了一种调频连续波SAR改进的频率尺度变换算法。调频连续波SAR在运动过程中持续不断地发射和接收信号,这种运动导致了回波信号的伸缩,对波前重建产生了严重的影响。推导了回波信号模型,给出了信号的距离-多普勒域表达式,分析了由于天线不断运动而导致的相位变化与方位向频率之间的关系。改进的频率尺度变换算法补偿了这种相位变化,实现了目标的精确成像,仿真结果表明了分析的正确性和算法的有效性。     

某型制导雷达部分元器件失效模式的分析

对某型号制导雷达部分元器件进行了失效分析，找出了导致元器件失效的原因，指出设计是提高可靠性的关键，并根据有关元器件情况对生产方与使用方提出了建议。着重讨论了设计师应注意的问题和应该遵循的设计原则。针对失效情况，提出了一些具体的设计构想。     

Real-Time Specifications of the Geospace Environment

We report the recent progress in our joint program of real-time mapping of ionospheric electric fields and currents and field-aligned currents through the Geospace Environment Data Analysis System (GEDAS) at the Solar-Terrestrial Environment Laboratory and similar computer systems in the world. Data from individual ground magnetometers as well as from the solar wind are collected by these systems and are used as input for the KRM and AMIE magnetogram-inversion algorithms, which calculate the two-dimensional distribution of the ionospheric parameters. One of the goals of this program is to specify the solar-terrestrial environment in terms of ionospheric processes, providing the scientific community with more than what geomagnetic activity indices and statistical models provide. This revised version was published online in August 2006 with corrections to the Cover Date.     

Space weather: its effects and predictability

Terrestrial technology is now, and increasingly, sensitive to space weather. Most space weather is caused by solar storms and the resulting changes to the Earth's radiation environment and the magnetosphere. The Sun as the driver of space weather is under intense observation but remains to be adequately modelled. Recent spacecraft measurements are greatly improving models of solar activity, the interaction of the solar wind with the magnetosphere, and models of the radiation belts. In-situ data updates the basic magnetospheric model to provide specific details of high-energy electron flux at satellite orbits. Shock wave effects at the magnetopause can also be coarsely predicted. However, the specific geomagnetic effects at ground level depend on the calculation of magnetic and electric fields and further improvements are needed. New work on physical models is showing promise of raising geomagnetic and ionospheric predictability above the synoptic climatological level. This revised version was published online in August 2006 with corrections to the Cover Date.     

Progress in space weather predictions and applications

The methods of today’s predictions of space weather and effects are so much more advanced and yesterday’s statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today’s applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.     

频率及频率变化率的快速最大似然估计

信号参数估计是许多领域 (如雷达、通信、导航和声钠等 )都会遇到的共同问题。文中证明 ,牛顿法是实现频率 (η)和频率变化 (β)最大似然估值器的快速有效算法 ,并且详细分析了牛顿估值器的性能。研究证明 ,对于牛顿法 ,(η,β)是以三次方律收敛于真值 (η,β)的。模拟结果表明 ,当输出信噪比 ( SNR) o≥ 15 d B时 ,估计量的均方误差 ( MSE)达到Cramer- Rao界     

逆合成孔径雷达信号处理方法研究进展

在简要评述国内外现有的逆合成孔径雷达（ISAR）信号处理的运动补偿和成象方法之后，介绍了南京航空航天大学ISAR课题组近年来在ISAR信号处理方法研究中取得的主要进展，包括基于多散射点定位观点的雷达成象观测模型，基于最大似然原理的同时运动补偿和成象方法，基于最大似然原理的多目标成象方法和基于时频分析的多目标成象方法，以及超分辩成象方法，文末指出了在ISAR信号处理方面有待进一步研究的问题。