基于稀疏约束的DCD滑动窗RLS水声信道估计算法研究

水声信道具有稀疏性的特点,因此高精度低复杂度的稀疏信道估计算法对水声通信具有重要意义.基于自适应滤波算法的信道估计问题本质上是线性回归模型参数的求解问题,传统的最小二乘(Least Square,LS)、最小均方(Least Mean Square,LMS)及递归最小二乘(Recursive Least Squares...     

基于未知系统动态估计器的柔性关节机械臂funnel控制

针对带有模型不确定和外部干扰的柔性关节机械臂,提出一种基于未知系统动态估计器的funnel控制方法.基于低通滤波器设计未知系统动态估计器,用于估计模型不确定和外部干扰,该估计器结构简单,仅有一个可调参数.构造带有时变约束边界的新型funnel变量,保证系统跟踪误差被限制在预先设定的边界内,进而改善系统瞬态性能.在此基础...     

一种水声通信中基于信道估计的假设反馈自适应均衡器

直接序列码分多址(DS/CDMA)是一种受关注的水下声通信网多址接入方案。提出一种基于信道估计的水声DS/CDMA系统自适应码片级均衡器。水声信道的时变特性要求自适应均衡器系数以码片速率更新,而不是以码元速率更新。在线性均衡之前利用信道估计器抑制由先前发送的码片引起的码片间干扰,仅对少量幅值较大的信道抽头做均衡,有效地降低了运算复杂度。仿真实验验证了均衡器的性能。     

一种适用于慢衰落信道OFDM系统的信道估计算法

针对慢衰落信道OFDM系统,提出了一种新的低复杂度的且能对抗定时误差的信道估计器.这种信道估计器是基于导频间隔I=2的特殊梳状导频结构设计的.基于工程实现的考虑,采用了最小平方(LS)算法进行导频信道估计,同时利用了线性内插对非导频信道进行估计.分析了定时误差对非导频子载波估计的影响,并提出了一种相当简单但十分有效的修正算法,仿真结果有力的证明了此算法能有效的抵抗定时误差对非导频信道插值估计的影响.     

多载波水声信道估计技术及其研究进展

简述了水声信道与正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统之间的必然联系,概述了基于导频符号的信道估计算法、自适应信道估计算法、子空间信道估计算法以及压缩感知稀疏信道估计方法在水声通信中的应用现状,总结了各种算法的特点,比较了各种算法的优缺点,并指出了未来水声信道估计的发展方向。     

具有多级自适应滤波器的有限元密度估计器

基于可能相关并具有某种遍厉性的样本数据,该文设计了一个具有多级自适应滤波器的有限元估计器去估计相应的(平稳)密度函数。数值例了表明了估计器的有效性。同时也讨论了一个有关估计器稳定性的性质。     

低比特率无线可视电话压缩编码方法研究

系统地研究了甚低比特率无线信道可视电话自适应压缩编码方法，其中包括帧间运动估计及运动补偿的范围和精度，自适应量比、传输缓存器和比特率控制、抗信道误码等。计算机模拟结果表明，此方法适于甚低比特率下无线可视电话的压缩编码，且恢复图像主观质量良好。     

一种信道估计动态更新的逐幸存路径处理算法

水声信道复杂的时变特性会影响水声通信系统的性能,在设计时需要进行特殊考虑。利用逐幸存路径处理算法在无需插入训练序列的情况下即可同时进行信道估计和数据检测的特点,提出了一种信道估计动态更新的算法。该算法通过比较当前时刻各条幸存路径的分支量度来判断信道变化的情况,从而决定信道估计更新的时刻,达到动态更新信道估计的目的。仿真结果表明,所提出的基于信道估计动态更新的逐幸存路径处理算法能有效地跟踪信道变化的情况,在时变信道中使用能获得较好的性能。     

OFDM水声通信系统动态OMP信道跟踪算法

针对正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)水声通信系统中最小二乘(Least Square,LS)信道估计算法和静态压缩感知信道估计算法分别存在估计精度低、导频开销大和计算复杂度高、实时性差的缺点,利用水声信道冲激响应的时域相关性,通过建立动态稀疏观测模型,提出一种动态正交匹配追踪(Dynamic Orthogonal MatchingPursuit,D-OMP)信道跟踪算法。该算法仅在初始时刻进行一次完整的正交匹配追踪(OrthogonalMatching Pursuit, OMP)信道估计获取信道支撑集,之后通过连续跟踪前一时刻信道支撑集的变化来跟踪信道。仿真结果表明,在导频开销相同的情况下,与传统LS算法、经典OMP算法相比,所提算法具有更好的信道跟踪性能和较低的算法复杂度。     

一种改进自适应陷波器在齿轮箱振动信号频率估计中的应用

针对多级齿轮系统振动主动控制所需参考信号的获取问题,设计一种基于变步长无偏平滑梯度算法的二阶IIR自适应陷波器。以实时振动信号为输入信号,通过调整陷波频率实现对齿轮啮合频率的在线估计,并采用自适应改变陷波器迭代步长的方法提高估计速度和精度,仿真验证了该陷波器相比传统自适应陷波器具有更快的估计速度和更小的稳态误差,与FFT和比值校正FFT两种方法比较,所提陷波器对频率变化具有更好的追踪性能;将两个陷波器串联构成级联陷波器组,通过二级齿轮箱的振动加速度信号对两个啮合基频分别进行在线的实时估计。实验结果显示级联陷波器组能快速且准确地估计对应啮合频率,且能实时追踪由于驱动和负载变动导致的啮合频率变化,证明所提方法在实际应用中的有效性。     

Using MBPE technique to accelerate solving the thin-wire EFIE used in numerical simulation of lightning

The antenna theory (AT) model is widely used to numerically simulate the propagation of current wave along lightning return-stroke channels and compute the radiated electromagnetic fields. In this model, the return stroke channel is considered as a vertical monopole antenna above perfectly conducting ground for which the numerical solution of the governing electric field integral equation (EFIE) in the frequency domain by the conventional method of moment (MoM) is prohibitively slow. In this paper, a model-based parameter estimation (MBPE) technique is proposed to reduce the number of frequency-domain calculation points required for the evaluation of space-time current distribution along a lightning return stroke channel. In applying this technique to a rational function model for the channel current distribution, a uniform-like sampling strategy is investigated. In order to accelerate the building of the moment impedance matrix, the reciprocal closed-form mutual impedance of sinusoidal electric dipoles and the symmetry of the model are used. The proposed technique is validated against the conventional inverse fast Fourier transform algorithm which uses a MoM solution for all frequencies within the channel base current spectrum. It is shown that considerable computation efficiency is achieved in terms of CPU time without losing accuracy.     

Channel estimation assisted by postfixed pseudo-noise sequences padded with zero samples for mobile orthogonal-frequency-division-multiplexing communications

A channel estimation (CE) technique that uses a postfixed pseudo-random sequence padded with zero samples is investigated to extend pseudo-random-postfix orthogonal-frequency-division-multiplexing (PRP-OFDM) communications onto mobile applications. The proposed technique takes advantage of pseudo-noise sequences periodically inserted after each OFDM block within the original guard interval (GI) in conventional zero-padded OFDM (ZP-OFDM) or within the original cyclic prefix (CP) in conventional CP-OFDM. This allows accurate estimation of the channel impulse response. In addition, the proposed technique takes advantage of the null samples padded after the PN sequences for reducing inter-symbol interference occurring with the CEs and with the overlap-add information detection in the conventional PRP-OFDM. The proposed technique successfully applies either (1) a least-squares (LS) CE with assistance from decision-directed data or (2) an approximate LS CE method onto PRP-OFDM-like communications for the purpose of improving CE performance on rapid time-varying channels. Computer simulations in conjunction with statistical analysis assess the performance evaluation of the proposed technique and show that it can achieve lower mean-square estimation errors and lower error probabilities in mobile environments.     

Kalman filter-based force estimation in a clamped plate using reduced order model and noisy measurements

Deterministic techniques are available for force estimation in dynamic systems in time, frequency, and modal domain. But, these techniques are susceptible to measurement noise and require an accurate model of the system, hence, are not suitable for precise force estimation. Some combined deterministic-stochastic approaches are available in the literature for unknown input force estimations, where force estimations are performed by considering the model uncertainty and measurement noise. In the present work, one such technique is extended by incorporating reduced-order model to estimate forces in of plate structures. Kalman filter and a recursive least-squares (KF-RLSE)-based technique which uses displacement and/or velocity measurements for force estimation is used in the present work with a reduced-order model. Time-varying unknown forces acting at single/multiple locations are reconstructed using the measured responses from the plate. Numerical simulation followed by experimental verification is presented. The effect of error in model parameters on the force estimation is presented, and robustness of the input estimation technique is tested for different levels of measurement noise.     

Optimization of Channel Estimation Using ELMx-based in Massive MIMO

In communication channel estimation, the Least Square (LS) technique has long been a widely accepted and commonly used principle. This is because the simple calculation method is compared with other channel estimation methods. The Minimum Mean Squares Error (MMSE), which is developed later, is devised as the next step because the goal is to reduce the error rate in the communication system from the conventional LS technique which still has a higher error rate. These channel estimations are very important to modern communication systems, especially massive MIMO. Evaluating the massive MIMO channel is one of the most researched and debated topics today. This is essential in technology to overcome traditional performance barriers. The better the channel estimation, the more accurate it is. This paper investigated machine learning (ML) for channel estimation. ML channel estimations based on the Extreme Learning Machine (ELMx) group are also implemented. These estimations, known as the ELMx group, include Regularized Extreme Learning Machine (RELM) and Outlier Robust Extreme Learning Machine (ORELM). Then, it was compared with LS and MMSE. The simulation results reveal that the ELMx group outperforms LS and MMSE in channel capacity and bit error rate. Additionally, this paper has proven complexity for verified computational times. The RELM method is less time consuming and has low complexity which is suitable for future use in large MIMO systems.     

无线城域网OFDM系统信道估计算法

OFDM技术是无线城域网IEEE802.16a标准中物理层面的主流调制技术,今建立符合IEEE802.16a标准的OFDM信道估计模型,阐述其导频基本信道估计方法的原理及特点,分析比较了LS/MMSE/LMMSE/SVD四种算法的MSE和BER性能特点.仿真结果说明,LMMSE算法的均方误差和误码率性能最好,且计算复杂度相对较低,易于物理实现.     

Formation of natural pH gradients in a microfluidic device under flow conditions: model and experimental validation

A new isoelectric focusing technique has been developed that incorporates natural pH gradient formation in microfluidic channels under flowing conditions. In conjunction, a one-dimensional finite difference model has been developed that solves a system of algebraic-ordinary differential equations that describe the phenomena occurring in the system, including hydrolysis at the electrodes, buffering effects of weak acids and bases, and mass transport due to both diffusion and electrophoresis. A quantitative, noninvasive, optically based method of monitoring pH gradient formation is presented, and the experimental data generated by this method are found to be in good agreement with model predictions. In addition, the model provides a theoretical explanation for initially unexpected experimental results. Model predictions are also shown to match well with experimental results of microfluidic isoelectric focusing of a single protein species. Accounting for the nonuniform velocity profile, characteristic of pressure-driven flow in microfluidic channels, is found to improve predictions of dynamic pH changes close to the electrodes and overall time required to reach steady state, but to reduce the accuracy of dynamic pH change predictions in other regions of the channel.     

基于逆系统分析法的多输入-多输出系统动态载荷的优化估计

本文提出了一种多输入－多输出系统动态的优化估计方法。该方法可以使估计的总体均方误差最小。首先,采用逆系统分析方法建立误差估计方程;其次,利用非因果维纳滤波理论导出了动态载荷的优化估计器。数字仿真结果表明,该方法在抑制测量噪声对估计精度的影响方面具有良好的效果。与传统方法估计结果的对比分析表明,所提出的方法更为有效和实用。     

Estimation of piezoelastic and viscoelastic properties in laminated structures

An inverse method for material parameter estimation of elastic, piezoelectric and viscoelastic laminated plate structures is presented. The method uses a gradient based optimization technique in order to solve the inverse problem, through minimization of an error functional which expresses the difference between experimental free vibration data and corresponding numerical data produced by a finite element model. The complex modulus approach is used to model the viscoelastic material behavior, assuming hysteretic type damping. Applications that illustrate the influence of adhesive material interfaces and viscoelastic parameter identification are presented and a few simulated test cases aid the interpretation of results.     

基于伪随机序列的多波束水声探测系统的信道估计技术

多波束水声探测系统不同方向回波信号的同时检测,可以理解为通信中的信道估计问题。在水下多径传播环境中,多径信道的时延参数和幅度衰减参数的估计是多波束探测系统实现目标探测、定位和识别的基础,而抑制来自其它波束的多址干扰(MAI)是信道估计算法的重要目标。将直接序列码分多址(Direct Sequence Code-Division Multiple Access,简称DS-CDMA)通信系统模型应用于水声多波束探测系统。建立了基于伪随机序列的水下多波束探测系统的信号模型,研究了基于子空间方法的超分辨率信道估计算法。并给出了数值仿真实现,分析了信噪比、多址干扰及发射波束数等对信道估计算法性能的影响。仿真结果表明,该算法具有抑制多址干扰的性能,信道参数的估计方差逼近Cramer-Rao下界。这种信道估计技术尤其适合应用于多波束参量阵探测系统。