前馈自适应射频功率放大器线性技术研究

介绍一种用于改善射频功率放大器非线性失真的前馈技术,并基于前馈系统,增加了自适应控制电路,提出使输出的交调信号功率最小化的方法来分别控制两个支路上的相位和幅度调节器,使系统性能稳定：本文较详尽地讨论了系统工作原理,通过ADS软件仿真．结果表明能显著改善IMD性能。     

射频放大器互调失真检测和载波抵消的研究

采用高功率射频信号内部互调失真的包络特性检测与比较技术,对射频功率带外信号进行检测和估计。设计用于高功率射频放大器前馈技术线性化的一个带外信号检测器。探讨如何进行射频载波抵消以及检测放大器互调失真信号。     

射频功率放大器前馈宽频带线性化技术的研究

针对第三代移动通信中的功率放大器线性化技术,提出了改善线性化带宽的解决方案。该方案通过减少前馈环路中的时延波动来提高互调失真分量的宽带对消特性,同时采用相关复解调来检测残留导频。研制了射频功率放大器,前馈对消环路和信号检测电路,用数字信号处理芯片实现了相关的自适应算法。仿真和实验结果表明,该技术能够在宽频带内对LDMOS高功率放大器的三阶互调(IMD3)改善25dB,对四载波的W-CDMA信号的邻近信道功率泄漏比(ACLR)改善17dB。     

基于导频检测技术的射频前馈功放研究

介绍了基于导频检测技术的前馈射频功放线性化技术,从理论上简单地分析了前馈功放以及利用导频信号自适应控制前馈功放的原理.利用导频法控制前馈有很多地电路结构,包括导频跳频、导频信号扩展和导频调制.导频法检测技术是一种简单而有效的控制技术,该技术的关键是选择合适的导频信号频率和信号的大小.通过对选定的最新的元器件,采用典型的导频前馈法用ADS进行仿真,并给出仿真结果,然后提出一个实际有效的导频法线性化方案.     

电子战信号环境仿真系统

论述了电子战信号环境仿真系统的组成方案及简要工作原理，详细阐述了电子战信号环境仿真系统射频通道单元的配置及其作用，以期对电子战信号环境仿真系统的设计提供一定的帮助。     

基于RF2422正交调制的分析与仿真

第3代移动通信系统采用了线性化调制方式,对放大器的线性度的要求也很高,因此设计一款高线性度的放大器有着十分重要的意义。针对前馈射频放大器设计中插入导频法自适应控制而采取的一种解决方法:通过RF2422正交调制双音频信号的载波信号作为导频信号,利用音频信号幅度的变化来控制幅度与相位变化,并利用ADS做出部分仿真。     

射频干扰对消技术的系统设计与仿真分析

针对现有大型电子信息系统中同平台接收设备受到同平台发射设备的发射干扰情况,研究了可对消发射设备干扰的射频干扰对消技术。分析了射频对消技术的理论模型,提出了射频对消技术的系统设计方案,重点研究了信号调整、信号检测和系统控制3个主要单元的设计和系统控制算法。系统仿真结果验证了该系统设计方法的正确性。该系统设计方法可用于进行后续的样机研制。     

一种高分辨力雷达扩展目标模拟系统设计与实现

针对高分辨力雷达扩展目标回波模拟，文中设计并实现了一种高分辨力雷达扩展目标模拟系统。建立了一维距离像目标、二维面目标、三维体目标的目标回波模型，结合宽带射频接收机技术、大瞬时带宽基带回波信号产生技术、目标RCS(Radar Cross Section)数据获取与调制技术以及宽带捷变频率合成器等关键技术完成了高分辨力雷达扩展目标模拟系统的设计与实现。使用该系统对某典型战斗机目标进行了射频仿真和二维成像处理，并将射频仿真和二维成像处理结果与使用RadBase仿真软件对该典型战斗机目标的仿真结果进行对比，验证了该系统的有效性。验证结果表明，该系统的射频仿真二维成像处理结果和RadBase仿真软件的仿真结果基本一致。     

相控阵技术对电子情报侦察影响研究

针对相控阵雷达技术引起的射频信号复杂多变的问题,提出一种基于对雷达射频信号进行动态信号级仿真的雷达侦察数据分析方法.对典型相控阵雷达系统应用的相控阵雷达技术进行了分析,并运用Matlab 7.0仿真工具软件对相控阵雷达射频信号进行了实时信号级仿真,获得了射频信号模型,分析了相控阵技术对电子情报侦察的影响.     

RFID发射前端的零中频电路设计

软件无线电技术增强了射频识别（RFID）系统的信号处理能力及兼容性,而零中频的设计思想进一步简化了射频前端结构。然而射频前端依然发挥着不可替代之重要功能,若在设计中将其地位置于软件子系统之下往往会恶化整体性能。本文对基于零中频技术的RFID射频发射前端进行了必要的理论分析,在此基础上,按照性能指标要求对系统进行了预增益仿真和谐波平衡仿真,以此作为模块选型和优化的依据,最后完成了射频前端设计。仿真结果表明,各项指标较为理想。     

Nonlinear identification and optimal feedforward friction compensation for a motion platform

In this study, we present a method of nonlinear identification and optimal feedforward friction compensation for an industrial single degree of freedom motion platform. The platform has precise reference tracking requirements while suffering from nonlinear dynamic effects, such as friction and backlash in the driveline. To eliminate nonlinear dynamic effects and achieve precise reference tracking, we first identified the nonlinear dynamics of the platform using Higher Order Sinusoidal Input Describing Function (HOSIDF) based system identification. Next, we present optimal feedforward compensation design to improve reference tracking performance. We modeled the friction using the Stribeck model and identified its parameters through a procedure including a special reference signal and the Nelder–Mead algorithm. Our results show that the RMS trajectory tracking error decreased from 0.0431 deg/s to 0.0117 deg/s when the proposed nonlinear identification and friction compensation method is utilized.     

Fast initialization of equalizers for VSB-based DTV transceivers in multipath channel

This paper proposes a fast initialization technique for equalization of 8-VSB-based digital television (DTV) signal in severe multipath channels. We consider the use of a modified decision feedback equalizer (MDFE) , for fast initialization. The feedback filter (FBF) of the MDFE can be initialized simply by estimating the channel impulse response and only the feedforward filter (FFF) of the MDFE need training for initialization. To overcome the shortage of the training sequence in the VSB DTV signal, we propose a new initialization method by generating a virtual training signal to initialize the FFF of the MDFE. Simulation results show that the proposed scheme can fast initialize the equalizer using less than 5000 symbols, while providing the receiver performance comparable to that of conventional schemes.     

Signal-error-feedforward-controlled amplifiers

Signal-error feedforward can be used to control the performance of amplifier systems. Feedforward, unlike feedback, does not require signal loops, and therefore results in inherently stable systems. Some practical feedforward-amplifier configurations are given, followed by a numerical example that demonstrates the improvement obtained from the application of signal-error feedforward.     

Joint input shaping and feedforward for point-to-point motion: Automated tuning for an industrial nanopositioning system

Feedforward control can effectively compensate for the servo error induced by the reference signal if it is tuned appropriately. This paper aims to introduce a new joint input shaping and feedforward parametrization in iterative feedforward control. Such a parametrization has the potential to significantly improve the performance for systems executing a point-to-point reference trajectory. The proposed approach enables an efficient optimization procedure with global convergence. A simulation example and an experimental validation on an industrial motion system confirm (i) the performance improvement obtained by means of the joint input shaping and feedforward parametrization compared to pre-existing results, and (ii) the efficiency of the proposed optimization procedure.     

Comparison of quasifeedforward- and feedback-controlled amplifier

In systems with signal-error feedforward, the recently suggested method of compensated signal takeoff can be used to extend the improvement of feedforward control to the output signal adder. A system using this quasifeedforward is compared with a feedback system consisting of similar components. The dynamic stability and the improvement obtained with both control methods are analysed.     

一种基于删余改进的码相差前馈估计方法

针对低载噪比下突发直扩信号扩频码相位估计问题,通过分析扩频码自相关函数Hilbert变换后特性,基于现有前馈估计方法,采用删余的思想改进得出了一种性能更优的前馈估计算法。仿真表明,与现有的几种前馈估计方法相比,本文算法码相差估计误差低于现有几种算法,可以有效提高低载噪比下码相差估计性能。     

Random vibration test control of inverter-fed electrodynamic shaker

The random vibration control of an inverter-fed electrodynamic shaker is presented in this paper. First, the dynamic model of the shaker is found and a current-controlled pulsewidth modulation inverter is designed and implemented. The feedback controller is augmented with a command feedforward controller and a disturbance feedforward controller to let the armature exciting current have low harmonic content and possess excellent waveform tracking performance. Then, an acceleration controller and its random vibration command are arranged. In the proposed acceleration control scheme, a command feedforward controller and a robust disturbance feedforward controller are also employed to let the shaker have close random acceleration command waveform tracking control performance, and the performance be insensitive to the system parameter variations. It follows that the acceleration control with desired frequency response in a vibration test could be achieved through properly setting the command signal. The effectiveness of the proposed control scheme is verified by simulation and measured results     

Parametric signal restoration using artificial neural networks

The problem of parametric signal restoration given its blurred/nonlinearly distorted version contaminated by additive noise is discussed. It is postulated that feedforward artificial neural networks can be used to find a solution to this problem. The proposed estimator does not require iterative calculations that are normally performed using numerical methods for signal parameter estimation. Thus high speed is the main advantage of this approach. A two-stage neural network-based estimator architecture is considered in which the vector of measurements is projected on the signal subspace and the resulting features form the input to a feedforward neural network. The effect of noise on the estimator performance is analyzed and compared to the least-squares technique. It is shown, for low and moderate noise levels, that the two estimators are similar to each other in terms of their noise performance, provided the neural network approximates the inverse mapping from the measurement space to the parameter space with a negligible error. However, if the neural network is trained on noisy signal observations, the proposed technique is superior to the least-squares estimate (LSE) model fitting. Numerical examples are presented to support the analytical results. Problems for future research are addressed     

一种复值函数型连接神经网络

本文提出了一种复值函数型连接神经网络(CFLNN)结构,可以对复数域信号进行快速处理。函数型连接神经网络通过对输入模式预先进行非线性扩展,增强了输入信号的模式表达,从而可以大为简化网络结构,降低计算复杂度。本文将函数型连接神经网络推广到了复值情况并给出了基于梯度下降的学习方法。计算复杂度分析显示本方法具有结构简单,计算量低的优点。最后,将本方法运用到对复值非线性系统的辩识问题中,仿真实验表明本CFLNN性能与传统复值前馈神经网络相近或更优。     

Buck型变换器的线性化小信号补偿前馈控制

为减小由输入电源扰动引起的输出电压工频纹波,改善DC/DC变换器动态性能,根据平均变量建模思想,为电压型PWM控制的Buck型变换器建立连续导电工作模式（CCM）下统一的平均变量等效电路。分析等效电路并根据前馈控制的不变性原理提出Buck型变换器针对输入电压扰动的线性化小信号补偿前馈控制原理及实现方法,采用该方法的Buck型变换器可快速补偿输入电压扰动,加快变换器在输入电压扰动时的动态调节过程,显著减小输出电压中包括工频在内的低频纹波,改善变换器的动态性能。仿真研究结果验证了文中线性化小信号补偿前馈控制原理、方法及其分析的正确性。