微波器件噪声参数的测量方法

作为微波低噪声器件研制和应用的一项关键技术,噪声参数的测量工作引起行业的广泛关注。论述了噪声参数测量原理,研究了测量系统校准方法,分析了噪声源的反射系数、噪声温度,阻抗调配器的反射系数、S参数、增益,接收机的反射系数、噪声功率等20余项物理量对噪声参数测量的影响,对比了直接冷源法和简化冷源法在接收机传输增益测量中的优缺点,提出了改进型冷源法。最后给出了噪声参数测量不确定度主要影响量的归类分析,为下一步开展噪声参数不确定度评定工作奠定了基础。     

二维位移测量中激光漂移实时补偿方法研究

激光漂移是影响二维位移测量精度的主要因素之一。为了消除激光光源漂移对二维位移测量结果的影响,提出了一种双光路激光漂移实时补偿的方法。在二维位移测量系统中,根据测量光路结构工作机理建立了激光光源平漂和角漂对位移测量产生误差的模型,通过参考光路监测激光的漂移量,并利用误差模型将漂移量经过转换后补偿到测量结果中。理论分析表明,本文方法能够实现对平漂和角漂的完全补偿。分析了实际光路布置中的结构参数误差对补偿效果的影响,基于此选择光路的结构参数。实验结果显示,使用双路激光漂移补偿方法后,可以使8h内的X方向和Y方向的漂移量分别减少55.1%和73.3%。     

工件特征在机测量的关键误差分析与补偿研究

针对激光在机测量工件特征时的测量精度问题,对测量系统的关键误差影响因素及补偿应用进行了研究。使用激光位移传感器作为测量工具对工件特征进行在机测量时,测量结果受激光位移传感器倾斜误差和数控机床几何误差影响。为了校正激光位移传感器在物面倾斜时引起的测量误差,设计了倾斜误差试验,利用勒让德多项式对倾斜误差进行了建模和补偿,补偿后倾斜误差可减小至±0.025 mm以内。针对不动式激光在机测量时数控机床线性轴几何误差对测量结果的影响,设计了球杆仪倾斜安装试验,利用参数化建模的方式对X轴和Y轴的几何误差进行了解耦。最后根据建立的倾斜误差与几何误差模型,对工件特征的在机测量结果进行了补偿。结果表明,对工件特征在机测量结果进行误差补偿后,线性尺寸测量误差小于0.05 mm,角度测量误差小于0.08°,相较于补偿前在机测量精度明显提高。     

数字增益自动补偿微波辐射计环境温度变化修正方法

数字增益自动补偿微波辐射计通过测量参考基准源相应的输出量的变化进行增益补偿,保证整机的稳定.在高灵敏度的需求下,为了克服控温电流波动对接收机的影响,采用了与机箱环境温度`相同的匹配负载作为参考源,因此参考源输出的噪声温度会随着机箱温度升高而变化,导致测量误差,需要采取环境温度变化修正方法消除此测量误差量,以保持系统的稳定.同时介绍了数字增益自动补偿微波辐射计基本原理、环境温度变化修正原理及方法,并对补偿后辐射计的稳定性进行了长期稳定性测量,实现了对大气特性的有效探测.     

大信号晶体管输出等功率曲线的搜索算法

结合Smith圆图,利用微波大功率自动调配器测试系统,采用负载牵引法,给出搜索等功率圆曲线的算法。此算法在可以确定的圆方程上进行搜索,避免了在整个圆图中搜索很多个点再进行圆回归拟合的繁琐。等增益、等噪声都是可以Smith圆图中表示的圆,因此,此算法对以后其他参数的圆图搜索也有实际意义。     

小波分析和灰色神经网络融合的光纤陀螺误差建模与补偿

为补偿捷联姿态测量系统中光纤陀螺因外界干扰引起的高频噪声和强漂移,提出一种基于第二代小波变换和灰色Elman神经网络融合的误差建模和补偿方法。采用Allan方差法分析了在外界干扰下的光纤陀螺输出信号,利用第二代提升小波单独重构的方法分离出陀螺误差模型中的漂移误差和白噪声,灰化漂移误差数据后建立了Elman神经网络模型并进行了补偿。实验结果表明,相较于传统的灰色理论模型和单一的Elman神经网络模型,新算法有效滤除了白噪声,并将预测模型的精度提高到96%以上,证实了模型的有效性。     

测量机器人在线动态温度误差补偿技术

为了降低温度变化对白车身激光视觉检测系统测量结果的影响,借助安装在工业机器人基座附近的靶标球,建立基于坐标值误差的温度误差补偿模型.同时考虑到机器人结构特点,分析了连杆参数变化规律,确定存在显著变化的参数.实验结果表明,使用这种标定方法可以使机器人重复定位精度接近标称水平,明显改善了测量系统的工作稳定性,满足在线动态补偿要求.     

基于激光干涉式水听器的近海海洋环境噪声测量研究

在迈克尔逊干涉原理的基础上设计了激光干涉式水听器,通过跟踪补偿的方式提高了水听器的抗干扰能力。通过对水听器声压误差进行分析,认为振动膜是声压误差的主要来源,且可以通过振动膜材料的选择得到一定程度上的消除。在某近海海域获得的实测数据表明,水听器对噪声声压的测量精度较高,具有良好的频率响应能力,与理论模型的对比实验也一定程度上验证了数据的准确性。在近海海域,风成噪声和船只辐射噪声是海洋环境噪声测量的主要噪声源。在此,对3种风速下测得的海洋环境噪声谱级进行了计算,并与Knudsen曲线进行了比对,结果显示,测量数据与Kundsen曲线拟合度较好,经测量,船只辐射噪声主要集中在350~500Hz频率范围内。     

光栅角编码器偏心误差修正方法研究

为了减小光栅角编码器偏心误差的影响,提高光栅角编码器角度测量的精度,对偏心误差的修正方法进行了研究。通过对光栅角编码器测角原理和偏心误差产生原因的分析,建立了偏心误差模型。并根据偏心误差模型的特点,对其进行简化,得到易于数学计算的偏心误差修正模型。以平行光管和23面棱体为基准,得到存在偏心误差的一组光栅角编码器测量数据。使用线性最小二乘参数选择准则,对偏心误差修正模型中的参数进行优化计算,得到修正模型中的参数,完成对光栅角编码器误差偏心的修正。通过误差修正试验和精度验证试验,表明经过偏心误差修正,系统测量精度优于±13″。修正方法达到了补偿误差的目的,提高了光栅角编码器的测量精度,满足了高精度角度测量的要求。     

MIMU随机误差分析与建模

分析了MEMS惯性测量组件(MIMU)的主要误差源,采用功率谱密度(PSD)法和Allan方差法对MIMU进行了随机误差分析、建模和估计研究。将随机误差中的量化噪声、闪烁噪声及随机游走噪声等误差成分分离出来,并对其统计特性进行了估计,实验数据分析表明闪烁噪声和随机游走误差在MIMU随机误差中占主要分量。     

微波放大器Rn-Gn模型噪声参数的准确提取

对微波放大器Rn—Gn噪声模型以及噪声参数的提取方法进行了研究,自行研制了精密的阻抗变换器,组建了一套新的噪声系数测量系统,采用加权最小二乘法准确提取出放大器的噪声参数。实验测量结果稳定、可靠,在不同频点下可以得到包括最小噪声系数在内的四个噪声参数,并节省了测量时间,为微波低噪声放大器的设计提供了更加可靠的基础数据。     

A Method for Measurement of Losses in the Noise-Matching Microwave Network While Measuring Transistor Noise Parameters

A new method for measuring the loss of a tuner network used as the noise-source admittance transformer in a noise parameter test set is presented. Since the method is based on noise figure measurements, the tuner losses are determined on-line while performing measurements for determining transistor noise parameters. Experiments carried out on a coaxial slide-screw tuner by means of a computer-assisted measurement setup are reported.     

A Complete Noise- and Scattering-Parameters Test-Set

We present an innovative test-set based on a microwave tuner, a vector network analyzer and a $Y$ -factor receiver capable of extracting the noise and the scattering parameters of a two-port device. To the authors' knowledge, the presented test-set is the first noise system that avoids the use of any microwave switch in the noise measurement branches. A set of reflectometers and a novel calibration scheme are used to measure the tuner's loss and $S$-parameters in real time without any tuner precharacterization.      

Mesure automatique des paramétres de bruit des MESFET hyperfréquences

An automatic noise parameter measurement test set is described in two sections : (i) A novel noise parameter extraction procedure from a set of noise figure measurements is developped. The experimental minimum noise figure is no longer required and the sensitivity to measurement incertainties is found to be very low. (ii) An automatic input tuner with a large number of precalibrated and reproducible positions is designed and realized. The last part give examples of broadband (8 to 17 GHz) noise parameters characterization ofmmic GaAsmesfets when both the automatic tuner and the extraction procedure are used.     

HE331型、HE341型、HE351型、微型超高频宽带混合集成放大电路

本文介绍了一种国际通用管壳封装的超小型混合集成放大电路。该电路采用薄膜混合集成技术,将微波管芯、薄膜电阻、平面螺旋电感等集成于一个φ8.4mm的B-3金属管壳之中。采用了负反馈加电抗补偿等集总参数设计,并提供了一种典型负反馈宽带低噪声放大器的简化计算方法。设计了一种用超声键合法在微型管壳内动态调试放大器的技术方法。     

FET noise-parameter determination using a novel technique based on50-Ω noise-figure measurements

A novel method for measuring the four noise parameters of a field-effect transistor (FET) is presented. It is based on the determination of its intrinsic noise matrix elements [C₁₁^INT, C₂₂^INT, Re(C₁₂ ^INT), Im(C₁₂^INT)] by fitting the measured device noise figure for a matched source reflection coefficient (F₅₀) at a number of frequency points, thus, a tuner is not required. In contrast to previous works, no restrictive assumptions are made on the intrinsic noise sources. The receiver full-noise calibration is easily performed by using a set of coaxial and on-wafer standards that are commonly available in a microwave laboratory, thus, an expensive broad-band tuner is not required for calibration either. On-wafer experimental verification up to 26 GHz is presented and a comparison with other F₅₀-based and tuner-based methods is given. As an application, the dependence of the FET intrinsic noise sources as a function of the bias drain-current and gate-length is obtained     

A wide-band on-wafer noise parameter measurement system at 50-75 GHz

A wide-band on-wafer noise parameter measurement system at 50-75 GHz is presented. This measurement system is based on the cold-source method with a computer-controlled waveguide tuner. Calibrations and measurement methods are discussed and measured results for passive and active on-wafer devices are shown over a 50-75 GHz range. An InP high electron-mobility transistor device is used as a test item for the active device. A Monte Carlo analysis to study measurement uncertainties is also shown. The measurement system is a useful tool in the development and verification of device noise models, as well as in device characterization.     

11.GHz GaAs Power MESFET Load-Pull Measurements Utilizing a New Method of Determining Tuner Y Parameters

A Ioad-pull technique utilizing a new method of determining tuner Y parameters is proposed for huge-signal characterization of microwave power transistors. Large-signal input-output transfer characteristics of an active circuit containing a GaAs FET and an input matching circuit are measured by inserting a microstrip tuner between the active circuit output drain terminal and the 50-Omega load. The microstrip-tuner Y parameters are determined by comparing the dc bias-dependent small-signal S parameter S/sub 22/ of the active circuit and that of the circuit which contains the active circuit and microstrip tuner. The reflection coefficient presented to the active circuit output drain terminal is derived from tuner Y parameters. Optimal load impedances for output power, obtained with this new Ioad-pull technique, are used to design X-band GaAs FET power amplifiers. An 11-GHz power amplifier with a 3000-mu m gate-width FET chip delivers 1-W microwave power output with 4-dB gain in the 500-MHz band.     

An improved model for noise characterization of microwave GaAs FETs

A broadband noise model for microwave FETs has been described. The model consists of small-signal lumped elements together with two noise sources. A measurement of broadband S parameters plus a single-frequency measurement of optimum source susceptance can yield enough information to determine the model, although greater accuracy is obtained using additional noise data to determine the precise value of the gate resistance. The model's predictions match well with measured noise parameter data for a high-performance GaAs FET over a wide frequency range