一种精准数控STC设计方法

介绍了雷达接收机中STC控制的产生背景、原理及方法,采用MATLAB语言进行仿真,重点介绍了一种基于电控衰减器作为受控部件的数字STC控制曲线的精确设计方法,并提出了雷达STC的设计和使用原则。     

复杂形体目标激光散射特征测量系统的研制

复杂形体目标激光散射特征的测量系统中，利用反射式离轴光路满足了可见到远红外波段的测量需要，通过大孔径（250mm）物方远心接收光路实现了对实际远场的模拟测量，以光滑镀金球体作为标准器，可直接获得任意目标散射截面的绝对值。在0．6328、1．06和10．6μm三个波段针对标准器的实测结果表明，平均误差小于4．95％。     

Multi-channel SAR imaging based on distributed compressive sensing

The rapid development of compressive sensing(CS)shows that it is possible to recover a sparse signal from very limited measurements.Synthetic aperture radar(SAR)imaging based on CS can reconstruct the target scene with a reduced number of collected samples by solving an optimization problem.For multi-channel SAR imaging based on CS,each channel requires sufficient samples for separate imaging and the total number of samples could still be large.We propose an imaging algorithm based on distributed compressive sensing(DCS)that reconstructs scenes jointly under multiple channels.Multi-channel SAR imaging based on DCS not only exploits the sparsity of the target scene,but also exploits the correlation among channels.It requires significantly fewer samples than multi-channel SAR imaging based on CS.If multiple channels offer different sampling rates,DCS joint processing can reconstruct target scenes with a much more flexible allocation of the number of measurements offered by each channel than that used in separate CS processing.     

利用Visual C＋＋和Direct3D设计雷达显示器

利用Visual C＋＋和Direct3D对某雷达显示器的实现过程作了详细论述,包括数据采集、PPI型显示器、A型显示器、B型显示器、余晖显示、航迹显示等。通过试验证明,采用Direct3D绘图方式比采用GDI绘图方式效果好,更适用于数据处理量大、天线扫描速度快的雷达显示器。     

Maximizing learning without sacrificing the fun: Stealth assessment,adaptivity and learning supports in educational games

In this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.     

Edge diffraction correction for 3D scattering center modeling based on the shooting and bouncing ray technique

In the traditional scattering center extraction method based on the shooting and bouncing ray(SBR) technique,only the physical optics contribution of the target is considered.However,the physical optics method is unable to describe the contribution of the actual edge diffraction.By comprehensively considering the specular reflection and edge diffraction contribution of the target,an edge diffraction correction method for 3D scattering center modeling based on the SBR technique is proposed.Using the SBR technique and combining the image domain ray tube integration and equivalent edge currents method,the edge diffraction correcting formula for the 3D inverse synthetic aperture radar image is derived.Simulation results show that the proposed method is able to effectively improve the modeling accuracy of the 3D scattering center.     

Method for discrimination of false targets in multistation radar systems based on the deep neural network

For the existing jamming discrimination methods for multistation radar systems,only the single feature of target echo space correlation is utilized as the metric,which leads to insufficient comprehensiveness of feature extraction,so that effectiveness and universality are insufficient for the discrimination algorithm.In this paper,an identification method in multistatic radar systems based on the deep neural network is proposed.This method combines the characteristics of multistatic radar systems cooperative detection technology,which has many available resources and strong scheduling ability in space,time and frequency domain,with the strong model learning and feature representation ability in the process of information processing on the deep neural network,so that it can effectively apply to the field of anti-deception jamming.Full use is made of unknown information about echo data to obtain more multi-dimensional,more comprehensive,more complete and deeper feature differences besides correlation,so as to achieve a better jamming discrimination effect.Simulation results show that the proposed method can effectively reduce the influence of noise and pulse number on the jamming discrimination performance.At the same time,the limitation of the target echo correlation coefficient on anti-jamming technology under nonideal conditions is alleviated,which broadens the boundary conditions of the application process.     

Estimating discharge in gravel‐bed river using non‐contact ground‐penetrating and surface‐velocity radars

Discharge measurement is a critical task for gravel‐bed channels. Under high‐flow conditions, the elevation of the riverbed changes significantly by intensive torrential flow. The stage–discharge relations commonly used for stream discharge estimation may no longer be adequate. The contact‐type velocity measuring is also subject to measurement errors and/or instrument failures by the high‐flow velocities, driftwood, stumps, and debris. This study developed a new real‐time method to estimate river discharge in gravel‐bed channels. A systematic measuring technology combining ground‐penetrating radar and surface‐velocity radar was employed. The rating curves representing the relations of water surface velocity to the channel cross‐sectional mean velocity and flow area were established. Stream discharge was then deduced from the resulting mean velocity and flow area. The proposed method was examined in a steep gravel‐bed reach of the Cho‐Shui River in central Taiwan. The estimated stream discharge during three flood events were compared to the prediction by using the stage–discharge relation and the index‐velocity method. The proposed method of this study is capable of computing reasonable values of discharge for an entire flood hydrograph, whereas the other two methods tend to produce large extrapolation errors. Moreover, when the computed discharge is used in 2D flood flow simulation, the proposed method demonstrates better performance than the commonly used stage–discharge and index‐velocity methods.