一种补偿量可调的反射式预失真线性化器

提出一种改进的反射式预失真电路,使其在相同功率区间上具有在线的补偿量调节能力。该电路对肖特基二极管不施加偏置电压,避免了因偏压改变而引起的补偿区间变化;在非线性产生电路中串联变容二极管,通过调节变容管的偏置电压,实现预失真器补偿量的调节。采用该方案设计加工了工作于29~31 GHz频段的反射式预失真器,实测结果表明:将变容管偏置电压由0调节至6 V,在相同功率区间内,该预失真器的增益扩张由4.5增大至7.6 d B,相位扩张由3.4°增大至51.1°。

用于固态功放反射式宽带预失真器设计方法

提出了一种特定增益和相位补偿的反射式宽带线性化器设计方法,并通过此方法设计了一种补偿固态功率放大器失真特性的预失真电路。利用肖特基二极管产生非线性补偿,根据电路拓扑结构,利用matlab优化工具找到单频点处特定增益补偿和相位补偿特性的并联负载值,改变频点,并重复上述步骤,可进一步得到特定增益和相位补偿所需的并联负载随频率的变化关系(即Z_(L)~f曲线)。利用ADS仿真软件优化设计使二极管后端阻抗随频率的变化逼近Z_(L)-f曲线。仿真的电路增益补偿和相位补偿分别为6 dB和−40°。最终实测频率范围为9.4~11.4 GHz,增益扩张在3.9~4.4 dB,相位补偿在−32.3°~−41.5°,频带特性良好,并且相对带宽达到了19.2%。通过改变二极管直流偏置电压,还实现了补偿曲线的斜率可调。

关于昆虫步态运动时神经控制机理的动力学分析

在John Schmitt和Philip Holmes工作基础上建立一个考虑阻尼效应的昆虫LLS(lateral leg-spring)模型,并在MATLAB环境下对其步态运动进行计算机数值模拟,对昆虫在水平面爬行步态进行分析,发现考虑阻尼的模型更符合实际情况,并表现出更好的稳定性,证明了由力学和几何定理主导的控制行为在维持昆虫爬行的稳定性方面起到了十分重要的作用,从而减轻了神经系统的负担,同时也说明了引入阻尼在提高运动稳定性方面发挥的作用.

基于被动力学的昆虫运动动力学建模与分析

在John Schmitt和Philip Holmes等人工作的基础上,基于被动力学建立了一个考虑阻尼效应的昆虫LLS (lateral leg-spring)爬行模型。通过在Matlab环境下对模型进行数值仿真,发现引入阻尼后的模型更加符合实际情况,并表现出较好的稳定性。证明在施加的控制作用十分有限的情况下,昆虫本身身体结构及其爬行姿态在维持运动的稳定性方面发挥着重要作用,事实上这样的控制策略具有重要的生物学意义,通过被动力学的机械反馈,生物体可以在有限的神经控制作用下保持稳定运动,从而在受到地面扰动时及时做出反馈,并提高能效性。同时,我们考虑了引入偏摆角扰动时系统的响应,发现相对于其他变量扰动,偏摆角可以有效地改变模型的前进方向,并具有较好的鲁棒性,提出了可能的方向控制策略。

Analysis of Physical Quantities and Radar Parameters about Hail Shooting and Heavy Convective Rainfall

[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ^（3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows： VIL value reaches 35 kg/m2 （May）, 43 kg/m2 （June and July）, the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km （May）, 4.3 km （June） and 5.5 km （July）; VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.

Fast Prediction of Acoustic Radiation from a Hemi-capped Cylindrical Shell in Waveguide

In order to predict acoustic radiation from a structure in waveguide, a method based on wave superposition is proposed, in which the free-space Green＇s function is used to match the strength of equivalent sources. In addition, in order to neglect the effect of sound reflection from boundaries, necessary treatment is conducted, which makes the method more efficient. Moreover, this method is combined with the sound propagation algorithms to predict the sound radiated from a cylindrical shell in waveguide. Numerical simulations show the effect of how reflections can be neglected if the distance between the structure and the boundary exceeds the maximum linear dimension of the structure. It also shows that the reflection from the bottom of the waveguide can be approximated by plane wave conditionally. The proposed method is more robust and efficient in computation, which can be used to predict the acoustic radiation in waveguide.

Estimation of As and Cu Contamination in Agricultural Soils Around a Mining Area by Reflectance Spectroscopy:A Case Study

Concentrations of Iron (Fe), As, and Cu in soil samples from the fields near the Baoshan Mine in Hunan Province, China, were analyzed and soil spectral reflectance was measured with an ASD FieldSpec FR spectroradiometer (Analytical Spectral Devices, Inc., USA) under laboratory condition. Partial least square regression (PLSR) models were constructed for predicting soil metal concentrations. The data pre-processing methods, first and second derivatives (FD and SD), baseline correction (BC), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR), were used for the spectral reflectance data pretreatments. Then, the prediction results were evaluated by relative root mean square error (RRMSE) and coefficients of determination (R 2 ). According to the criteria of minimal RRMSE and maximal R 2 , the PLSR models with the FD pretreatment (RRMSE = 0.24, R 2 = 0.61), SNV pretreatment (RRMSE = 0.08, R 2 = 0.78), and BC-pretreatment (RRMSE = 0.20, R 2 = 0.41) were considered as the final models for predicting As, Fe, and Cu, respectively. Wavebands at around 460, 1 400, 1 900, and 2 200 nm were selected as important spectral variables to construct final models. In conclusion, concentrations of heavy metals in contaminated soils could be indirectly assessed by soil spectra according to the correlation between the spectrally featureless components and Fe; therefore, spectral reflectance would be an alternative tool for monitoring soil heavy metals contamination.

^5He Emission in Neutron-Induced ^10B Reactions

In n ＋^10B reactions, ^5He cluster emission has been discussed with the updated level scheme and the new optical model parameters. In this paper the reaction channels related to ^5He emission are listed in detail. By using the new reaction model for light nuclei, the double-differential cross sections of total outgoing neutrons for n ＋ ^10 B reactions at En= 14.2 MeV have been calculated, and the results agree fairly well with the measurements. Particularly, in the energy-angular spectra the contribution from the 5He-emission to the total outgoing neutron double-differential cross sections has also been analyzed, and the partial energy-angular spectra of 60° at En= 14.2 MeV have been given. The calculated results indicate that once the 5He emission is taken into account, the fitting with the double-differential measurements of total outgoing neutrons at the low energy region could be improved. Therefore, to consider the ^5He emission properly in the reaction processes of light nuclei is necessary.

Radar Cross Section Prediction and Reduction for Naval Ships

Radar cross section（RCS） is the measurement of the reflective strength of a target.Reducing the RCS of a naval ship enables its late detection,which is useful for capitalizing on elements of surprise and initiative.Thus,the RCS of a naval ship has become a very important design factor for achieving surprise,initiative,and survivability.Consequently,accurate RCS determination and RCS reduction are of extreme importance for a naval ship.The purpose of this paper is to provide an understanding of the theoretical background and engineering approach to deal with RCS prediction and reduction for naval ships.The importance of RCS,radar fundamentals,RCS basics,RCS prediction methods,and RCS reduction methods for naval ships is also discussed.

Spectral decomposition method for predicting magmatic intrusion into a coal bed

Accurate prediction of magmatic intrusion into a coal bed is illustrated using the method of seismic spectral decomposition.The characteristics of coal seismic reflections are first analyzed and the effect of variable time windows and domain frequencies on the spectral decomposition are examined.The higher domain frequency of coal bed reflections using the narrower STFT time window,or the smaller ST scale factor,are acceptable.When magmatic rock intrudes from the bottom of the coal bed the domain frequency of the reflections is decreased slightly,the frequency bandwidth is narrowed correspondingly,and the response from spectral decomposition is significantly reduced.Intrusion by a very thin magmatic rock gives a spectral decomposition response that is just slightly less than what is seen from a normal coal bed.Results from an actual mining area were used to validate the method.Predicting the boundary of magmatic intrusions with the method discussed herein was highly accurate and has been validated by observations from underground mining.

Predicting Surface Roughness and Moisture of Bare Soils Using Multi- band Spectral Reflectance Under Field Conditions

Soil surface roughness, denoted by the root mean square height(RMSH), and soil moisture(SM) are critical factors that affect the accuracy of quantitative remote sensing research due to their combined influence on spectral reflectance(SR). In regards to this issue, three SM levels and four RMSH levels were artificially designed in this study; a total of 12 plots was used, each plot had a size of 3 m × 3 m. Eight spectral observations were conducted from 14 to 30 October 2017 to investigate the correlation between RMSH, SM, and SR. On this basis, 6 commonly used bands of optical satellite sensors were selected in this study, which are red(675 nm), green(555 nm), blue(485 nm), near infrared(845 nm), shortwave infrared 1(1600 nm), and shortwave infrared 2(2200 nm). A negative correlation was found between SR and RMSH, and between SR and SM. The bands with higher coefficient of determination R^2 values were selected for stepwise multiple nonlinear regression analysis. Four characterized bands(i.e., blue, green, near infrared, and shortwave infrared 2) were chosen as the independent variables to estimate SM with R^2 and root mean square error(RMSE) values equal to 0.62 and 2.6%, respectively. Similarly, the four bands(green, red, near infrared, and shortwave infrared 1) were used to estimate RMSH with R^2 and RMSE values equal to 0.48 and 0.69 cm, respectively. These results indicate that the method used is not only suitable for estimating SM but can also be extended to the prediction of RMSH. Finally, the evaluation approach presented in this paper highly restores the real situation of the natural farmland surface on the one hand, and obtains high precision values of SM and RMSH on the other. The method can be further applied to the prediction of farmland SM and RMSH based on satellite and unmanned aerial vehicle(UAV) optical imagery.

Factors affecting the dynamic response of pre-stressed anchors after transient excitation

The wide application of pre-stressed bolting technology in coal mine tunnels has made the nondestructive stress wave reflection method of determining bolting quality an important one. The effect of the support plate on the dynamic response of the pre-stressed anchor is of particular interest. A theoretical analysis and numerical simulations are used to identify the factors affecting the contact stress between the support plate and the rock wall. A formula allowing the calculation of contact stress is presented. Stress wave propagation through the nut, support plate, and rock wall are predicted. The dynamic response signals were measured in the field using prestressed anchors pre-tightened to different torques. The effects from the support plate on the dynamic response were recorded and the results compared to the predictions of pre-stressed anchor. This work provides a theoretical reference for the signal processing of dynamic reflected wave signals in anchor bolts.

Estimating biophysical parameters of rice with remote sensing data using support vector machines

Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.