Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

The Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind conditions.To suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray images.In this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(RS)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is maximized.Two assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus RSis nea rly equal to the radius of the magneto pause curvature.We create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson noise.We then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea ks.From the filte red images,we calculate RS and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground truth.Our method estimates RS with an accuracy of<0.3 RE when the solar wind density exceeds>10 cm-3.The accuracy improves for greater solar wind densities and during southward interplanetary magnetic fields.The method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field turnings.Consequently,the technique will enable quantitative analysis of the magnetopause motion and help reveal the dayside reconnection modes for dynamic solar wind conditions.This technique will suppo rt the LEXI and SMILE missions in achieving their scientific o bjectives.

A Passive Low-Pass Filter on Low-Loss Substrate

The loss mechanisms of different passive devices （on-chip inductors and capacitors） on different substrates are analyzed and compared. OPS （oxidized porous silicon） and HR （high-resistivity） substrates are used as low-loss substrates for on-chip planar LPF （low pass filter） fabrication. For the study of substrate loss, a planar coil inductor is also designed. Simulation results show that Q （the quality factor） of the inductor on both substrates is over 20. Measurements of the LPF on OPS substrate give a - 3dB bandwidth of 2.9GHz and a midband insertion loss of 0.87dB at 500MHz. The LPF on HR substrate gives a - 3dB bandwidth of 2.3GHz and a midband insertion loss of 0.42dB at 500MHz.

Design of a compact low-pass filter with wide stopband

This paper presents a novel low-pass filter （LPF） with sharp rejection, wide stopband and compact size, which are realized by the defected ground structure （DGS） and the defected microstrip structure （DMS）. The equivalent circuit model is proposed and the circuit parameters are extracted by the circuit simulation software. The parameters measured are 3 dB cutoff frequency fc of 5.2 GHz, the insertion loss less than 0.5 dB from DC to 4.0 GHz and S21 less than -20 dB within the wide stopband from 6 GHz to 16 GHz. The results of the circuit optimization agree well with those of the full wave simulation and the measured ones, which validate the effectiveness of the equivalent circuit model. The size of the proposed LPF is decreased compared with normal LPF. This LPF can be applied in rectennas to eliminate high order harmonics.

Design of low-pass filter based on a novel defected ground structure

A novel defected ground structure （DGS） for the microstrip line is proposed in this paper. The DGS lattice has more defect parameters so that it can provide better performance than the conventional dumbbell-shaped DGS. Selectivity is improved by 97.2% with a sharpness factor of 24.6%. The method is applied to the design of a low-pass filter to confirm validity of the proposed DGS.

Compact Metamaterial Microstrip Low-Pass Filter

Complimentary hexagonal-omega structures are used to design compact, low insertion loss (IL), low pass filter with sharp cut-off. It has been designed for improvement of roll-off performance based on both μ and ε negative property of the complimentary hex-omega structure while maintaining the filter pass-band performance. By properly designing and loading the hexagonal-omega structure in the ground of microstrip line not only improve the roll-off of the low pass filter, but also reduced the filter size. The simulated results indicate that the proposed filter achieves a flat pass band with no ripples as well as selectivity of 19.68 dB/GHz, corresponding to 5-unit cells hex-omega structures. This significantly exceeds the 5.6 dB/GHz selectivity of the conventional low pass filter design, due to sub-lambda dimensions of the hex-omega structure. A prototype filter implementing area is: 0.712λg x 0.263λg, λg being the guided wavelength at 3-dB cut-off frequency (fc). The proposed filter has a size smaller by 36.2%.

Microstrip Low-Pass Elliptic Filter Design Based on Implicit Space Mapping Optimization

It is a time-consuming and often iterative procedure to determine design parameters based on fine, accurate but expensive, models. To decrease the number of fine model evaluations, space mapping techniques may be employed. In this approach, it is assumed both fine model and coarse, fast but inaccurate, one are available. First, the coarse model is optimized to obtain design parameters satisfying design objectives. Next, auxiliary parameters are calibrated to match coarse and fine models’ responses. Then, the improved coarse model is re-optimized to obtain new design parameters. The design procedure is stopped when a satisfactory solution is reached. In this paper, an implicit space mapping method is used to design a microstrip low-pass elliptic filter. Simulation results show that only two fine model evaluations are sufficient to get satisfactory results.

Comparative Study of Low-Pass Filter and Phase-Locked Loop Type Speed Filters for Sensorless Control of AC Drives

High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase-locked loop(PLL)type filters with respect to ramp speed reference tracking and steady-state performances,as well as the achievement of adaptive cutoff frequency control.An improved LPF-based filter structure with no ramping and steady-state errors caused by filter parameter quantization effects is proposed,which is suitable for applying LPF for sensorless drives of AC machines,especially when fixed-point digital signal processor is selected e.g.in mass production.Furthermore,the potential of adopting PLL for speed filtering is explored.It is demonstrated that PLL type filters can well maintain the advantages offered by the improved LPF.Moreover,it is found that the PLL type filters exhibit almost linear relationship between the cutoff frequency of the PLL filter and its proportional-integral(PI)gains,which can ease the realization of speed filters with adaptive cutoff frequency for improving the speed transient performance.The proposed filters are verified experimentally.The PLL type filter with adaptive cutoff frequency can provide satisfactory performances under various operating conditions and is therefore recommended.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Improved Strategy of Grid-Forming Virtual Synchronous Generator Based on Transient Damping

The grid-forming virtual synchronous generator(GFVSG)not only employs a first-order low-pass filter for virtual inertia control but also introduces grid-connected active power(GCAP)dynamic oscillation issues,akin to those observed in traditional synchronous generators.In response to this,an improved strategy for lead-lag filter based GFVSG(LLF-GFVSG)is presented in this article.Firstly,the grid-connected circuit structure and control principle of typical GFVSG are described,and a closed-loop small-signal model for GCAP in GFVSG is established.The causes of GCAP dynamic oscillation of GFVSG under the disturbances of active power command as well as grid frequency are analyzed.On this basis,the LLF-GFVSG improvement strategy and its parameter design method are given.Finally,the efficiency of the proposed control strategy in damping GCAP dynamic oscillations under various disturbances is verified using MATLAB simulations and experimental comparison results.

有源与无源滤波器教学中的对比分析方法

笔者在有源滤波器教学中 ,放弃了一般教科书常用的分析模式 ,尝试了一种新方法 ,即有源滤波器与无源滤波器对比分析的方法 ,并利用等效电路及相应的传输函数 ,重点突出了滤波网络中的“源”,清楚地验证了引入“源”以后的滤波器其 Q值是大于无源滤波器的。

脑保护滤网下支架治疗老年高危症状性颈动脉狭窄的疗效观察

目的探讨脑保护滤网下支架治疗老年高危症状性颈动脉狭窄的有效性和安全性。方法在脑保护滤网下对25例60岁以上的高危症状性颈动脉狭窄患者进行颈动脉支架成形(CAS)治疗。结果颈动脉病变残余狭窄≤20%,手术成功率达100%,临床症状消失。24例在围手术期均有不同程度心率、血压下降,但无严重并发症。结论脑保护滤网下支架治疗老年高危症状性颈动脉狭窄是安全、有效的。

高速智能车辆状态观测器设计

基于JLUIV Ⅳ型智能车辆状态变量vy(车辆侧向速度)的不可测性,结合二自由度转向动力学模型和预瞄运动学模型建立了Kalman滤波模型,并运用Kalman滤波理论设计了状态观测器。仿真和实验结果表明:该状态观测器对模型中不确定参数和事变参数具有良好的适应性,可满足车辆导航控制的要求。

新型BST薄膜可调带阻滤波器

提出了一种基于共面传输线结构的新型带阻滤波器,利用该结构在沉积有钛酸锶钡(BST—0.5)薄膜的氧化镁基片上设计并制作了一个可调带阻滤波器。测试结果表明,在30V的外加偏压下,带阻滤波器的传输特性曲线向高频方向整体移动了190MHz,其形状基本保持不变。

一种基于Directshow的实时运动监测系统的实现

采用Directshow框架,对运动检测的传统模型提出了简化和改进,设计了一个功能较完整的运动检测Fitler,用在网络视频监控项目中,得出了实验结果。

基于声光调谐滤光器的在线汽车尾气检测系统

传统的汽车尾气检测方法需要车辆停车并将测试探头插入汽车的排气管内进行检测,检测效率低下．声光调谐滤光器(AOTF)作为一种新型色散元件通过电调谐实现波长扫描从而具有在线检测功能．基于声光调谐滤光器设计一种新型的在线汽车尾气检测系统．该系统可以实现对汽车尾气中HC、CO和CO_2的含量进行在线检测,另外有数码相机对尾气排放量超标车辆的牌号进行拍照．该系统可以设置在十字路口对汽车尾气进行在线检测,提高检测效率,同时可以通过通讯系统使数据在环保相关领域实现共享．

基于模糊PID卡尔曼滤波的多传感信息融合移动机器人定位研究

当工业移动机器人处于复杂工作环境中,其信息序列误差随各量测噪声特性的变化而增大,若使用卡尔曼滤波器进行多传感信息融合则很难做到实时测量和调整,融合后的误差也随之倍增。为解决此问题,在卡尔曼滤波融合前引入增量式模糊自适应PID控制,通过模糊规则设计,改善滤波噪声方差,对融合信息进行限制,并对限制后的速度信号和加速度信号进行融合,从而提高控制精度。MATLAB系统仿真显示,所设计的控制器对多传感器的信息融合效果良好。

Research on SINS Alignment Algorithm Based on FIR Filters

An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misalignment case. An alignment scheme comprising a coarse phase by the IFBA method and a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.

Vertical structure and seasonal variation of tidal and residual currents in the northern Huanghai Sea

Analysis of tidal current and sea level has been made based on the observations from the summer of 2006 to the winter of 2007,respectively.The result indicates that a two-layer structure of residual current exists in summer,with its upper layer going northwestward and the lower layer southeastward.In addition,some strong residuals exist in the neighboring depth of the pycnocline during the current period of astronomical tide.In winter,except some individual layersthe residual currents mostly direct to the northwest,from which we can see the fluctuation of abnormal sea-level and the appearance of associated current because of the changes of the wind field.The analysis of tidal ellipse indicates that the direction of the maximum semidiurnal component is clockwise from summer to winter,with an angle of 16-18.Moreover,in summer the semidiurnal component rotates with depth clockwise while the diurnal component counterclockwise.However,the vertical structure is almost homogeneous in winter.

Memristor bridge-based low pass filter for image processing

This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform (SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto- noise ratio (PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.

Influence of Tire Dynamics on Slip Ratio Estimation of Independent Driving Wheel System

The independent driving wheel system, which is composed of in-wheel permanent magnet synchronous motor（I-PMSM） and tire, is more convenient to estimate the slip ratio because the rotary speed of the rotor can be accurately measured. However, the ring speed of the tire ring doesn’t equal to the rotor speed considering the tire deformation. For this reason, a deformable tire and a detailed I-PMSM are modeled by using Matlab/Simulink. Moreover, the tire/road contact interface（a slippery road） is accurately described by the non-linear relaxation length-based model and the Magic Formula pragmatic model. Based on the relatively accurate model, the error of slip ratio estimated by the rotor rotary speed is analyzed in both time and frequency domains when a quarter car is started by the I-PMSM with a definite target torque input curve. In addition, the natural frequencies（NFs） of the driving wheel system with variable parameters are illustrated to present the relationship between the slip ratio estimation error and the NF. According to this relationship, a low-pass filter, whose cut-off frequency corresponds to the NF, is proposed to eliminate the error in the estimated slip ratio. The analysis, concerning the effect of the driving wheel parameters and road conditions on slip ratio estimation, shows that the peak estimation error can be reduced up to 75% when the LPF is adopted. The robustness and effectiveness of the LPF are therefore validated. This paper builds up the deformable tire model and the detailed I-PMSM models, and analyzes the effect of the driving wheel parameters and road conditions on slip ratio estimation.