方位向非均匀采样对多通道天线星载SAR成像性能的影响

方位向周期性非均匀采样是多通道天线星载SAR系统设计时需要考虑的一个重要因素。针对多通道天线星载SAR系统中存在的方位向周期性非均匀采样对成像性能的影响进行了分析。在建立多通道天线星载SAR回波信号模型的基础上,根据成对回波理论和匹配滤波原理推导了由方位向周期性非均匀采样所造成的虚假目标位置与强度的计算公式,并结合成像处理过程分析了二维成像处理算法对虚假目标的影响,给出了二维成像处理后所得到的虚假目标强度计算公式。最后,通过计算机仿真验证推导与分析的正确性。     

复调制ZFFT的TMS320C25实现

介绍了用ＴＭＳ３２０Ｃ２５数字信号处理器实现复调制ＺｏｏｍＦＦＴ（ＺＦＦＴ）频率细化技术，在所举的例子中，用１０２４复数点选带ＦＦＴ获得通常８１９２复数点基带ＦＦＴ的频率分辨力。实验结果表明，此种频率细化方法特别适用于不能同时处理Ｎ点，而又要求Ｎ点ＦＦＴ频率分辨力的频谱分析场合，文中给出了几种提高Ｃ２５ＦＦＴ运算速度的方法，使１０２４复数点ＦＦＴ的运算时间减少到１２．６ｍｓ，可供工程应用参考。     

基于ICCD的空间微光成像系统成像性能研究

研究基于像增强型CCD（ICCD）的空间高分辨率微光成像系统的成像性能。通过理论推导及数学仿真的方法，对系统在微光条件下的能量传递、极限分辨力、信噪比以及调制传递函数进行分析计算。研究表明，系统在黎明照度条件下具有较好探测能力，通过对ICCD器件制冷可以有效提高系统信噪比，实现满月照度的探测成像。     

Mitigation of receiver biases in ionospheric observables from PPP with ambiguity resolution

PPP (Precise Point Positioning) is a GNSS (Global Navigation Satellite Systems) positioning method that requires SSR (State Space Representation) corrections in order to provide solutions with an accuracy of centimetric level. The so-called RT-PPP (Real-time PPP) is possible thanks to real-time precise SSR products, for orbits and clocks, provided by IGS (International GNSS Service) and its associate analysis centers such as CNES (Centre National d'Etudes Spatiales). CNES SSR products also enable RT-PPP with integer ambiguity resolution. In GNSS related literature, PPP with ambiguity resolution (PPP-AR) in real-time is often referred as PPP-RTK (PPP – Real Time Kinematic). PPP-WIZARD (PPP - With Integer and Zero-difference Ambiguity Resolution Demonstrator) is a software that is made available by CNES. This software is capable of performing PPP-RTK. It estimates slant ionospheric delays and other GNSS positioning parameters. Since ionospheric effects are spatially correlated by GNSS data from active networks, it is possible to model and provide ionospheric delays for any position in the network coverage area. The prior knowledge ionospheric delays can reduce positioning convergence for PPP-RTK users. Real-time ionospheric models could benefit from highly precise ionospheric delays estimated in PPP-AR. In this study, we demonstrate that ionospheric delays obtained throughout PPP-AR estimation are actu ally ionospheric observables. Ionospheric observables are biased by an order of few meters caused by the receiver hardware biases. These biases prohibit the use of PPP-WIZARD ionospheric delays to produce ionospheric models. Receiver biases correction is essential to provide ionospheric delays while using PPP-AR based ionospheric observables. In this contribution, a method was implemented to estimate and mitigate receiver hardware biases influence on slant ionospheric observables from PPP-AR. In order to assess the proposed approach, PPP-AR data from 12 GNSS stations were processed over a two-month period (March and April 2018). A comparison between IGS ionospheric products and PPP-AR based ionospheric observables corrected for receiver biases, resulted in a mean of differences of −39 cm and 51 cm standard deviation. The results are consistent with the accuracy of the IGS ionospheric products, 2–8 TECU, considering that 1 TECU is ~16 cm in L1. In another analysis, a comparison of ionospheric delays from 5 pairs of short baselines GNSS stations found an agreement of 0.001 m in mean differences with 22 cm standard deviation after receiver biases were corrected. Therefore, the proposed solution is promising and could produce high quality (1–2 TECU) slant ionospheric delays. This product can be used in a large variety of modeling approaches, since ionospheric delays after correction are unbiased. These results indicate that the proposed strategy is promising, and could benefit applications that require accuracy of 1–2 TECU (~16–32 cm in L1).     

IMPROVEMENT OF PHASE GRADIENT AUTOFOCUS ALGORITHM

ＩＭＰＲＯＶＥＭＥＮＴＯＦＰＨＡＳＥＧＲＡＤＩＥＮＴＡＵＴＯＦＯＣＵＳＡＬＧＯＲＩＴＨＭＬｉＬｉｗｅｉ（李立伟），ＭａｏＳｈｉｙｉ（毛士艺），ＡｓｉｆＲａｚａ，ＬｉｕＹｉｎｇ（刘莹）（ＤｅｐａｒｔｍｅｎｔｏｆＥｌｅｃｔｒｏｎｉｃＥｎｇｉｎｅｅｒｉｎｇ...     

Scientific requirements for future spatially resolved white-light and broad-band high-cadence observations of the Sun

Several important issues are open in the field of solar variability and they wait their solution which up to now was attempted using critical ground-based instrumentations. However, accurate photometric data are attainable only from space. New observational material should be collected with high enough spatial and spectral resolution, covering the whole visible range of the electromagnetic spectrum as well infrared and ultraviolet to reconstruct the total solar irradiance: (1) the absolute contributions of different small-scale structural entities of the solar atmosphere from the white light flares and from micro-flares are still poorly known; (2) we do not know the absolute contributions of different structural elements of the solar atmosphere to the long-term and to the cyclic variations of the solar irradiance, including features of the polar regions of the Sun; (3) the variations of the chromospheric magnetic network are still poorly evaluated; (4) only scarce information is available about the spectral variations of different small-scale features in the high photosphere. Variability of the Sun in white light can be studied with higher spectral, spatial and time resolution using space-born telescopes, which are more appropriate for this purpose than ground based observatories because of better seeing conditions, no interference of the terrestrial atmosphere and a more precise calibration procedure. Scientific requirements for such observations and the possible experimental tools proposed for their solution. Suggested solar studies have broader astrophysical importance.     

Developing a dust storm detection method combining Support Vector Machine and satellite data in typical dust regions of Asia

Enhancing the dust storm detection is a key part for the environmental protection, human healthy and economic development. The goal of this paper is to propose a new Support Vector Machine (SVM)-based method to automatically detect dust storms using remote sensing data. Existing methods dealing with this problem are usually threshold-based that are of great complexity and uncertainty. In this paper we propose a simple and reliable method combining SVM with MODIS L1 data and explore the optimal band combinations used as the feature vectors of SVM. The developed method was evaluated by MODIS and OMI data qualitatively and quantitatively on three study sites located in the Arabian Desert, Gobi Desert and Taklimakan Desert, and it was also compared to three other traditional methods based on their accuracy, complexity, reliability and sensitivity to thresholds. The detection results demonstrated that the combination of (Band7 − Band3)/(Band7 + Band3) ((B7 − B3)/(B7 + B3)), Band20 − Band31 (B20 − B31), and Band31/Band32 (B31/B32) can detect the dust storms more precisely than other individual bands or their combination. The comparison among those cases indicated that the proposed automatic method exhibited an advantage of minimizing the uncertainty and complexity, which were the limits of defining thresholds based on the threshold-based methods. The conclusions can provide references for studies that focus on statistical-based dust storm detection.     

基于遗传算法的一种高分辨率雷达目标识别方法

目标识别是防空信息处理中的一个重要环节,而对空中目标类型的识别还没有成熟的理论。通过对高分辨雷达回波信号的分析,在遗传算法的基础上,提出了一种高分辨雷达目标识别方法,由此进行目标识别。仿真实验结果表明,该方法具有高的识别率和强的抗干扰能力。     

域名系统的性能优化方案

针对当前域名系统 ,通过分析其工作过程和域名解析的原理 ,指出其性能优化的方向。改进域名数据库的组织结构可以优化本地查询 ,采用缓存技术和多副本技术可以优化远程查询 ,通过对远程查询和本地查询的优化 ,从而缩短域名解析时间 ,提高域名系统的工作效率。     

基于图像奇异值描述的雷达目标识别方法

利用目标对常规雷达发射波形的调制效应，先对录取的回波数据进行预处理，把一维回波序列投影成二维灰度图像，然后提取这种图像的反映飞机目标不同机型(大、小)和不同架次的奇异值作为特征矢量，采用BP神经网络对目标进行分类识别试验，结果表明该方法是有效的，这为常规低分辨雷达空中目标识别提供了一种新方法。