小波域视频运动估计研究进展

小波域运动估计技术作为基于小波的视频编码器中最关键的技术之一,成为近年来研究的热点．文章首先对比论述了空间域运动估计技术的不足和小波域运动估计技术的优势,然后以小波域运动估计技术的发展为主线,将目前的研究方法归纳为三类：对子带直接运动估计技术、子带间接运动估计技术和克服平移可变性的运动估计技术,并对三类运动估计方法的发展进行了概括性阐述和比较性研究,对三类方法中各种算法的适用范围、优势和所存在的问题进行了深入的讨论,在此基础上对小波域运动估计技术的未来发展趋势进行了展望．     

基于压缩感知的OQAM/OFDM系统POP方法信道估计

针对偏移正交幅度调制的正交频分复用(OQAM/OFDM)系统中成对训练序列(POP)法信道估计技术性能较差且受噪声影响较大的问题,提出了一种基于压缩感知(CS)的POP信道估计方法.该方法将压缩感知技术应用于POP法信道估计之中,将传统的频域信道估计方法转化为时域信道估计方法,通过压缩感知技术准确地重构出时域信道信息,减少导频开销,提高频谱利用率,得到更好的信道估计性能.与传统的OQAM/OFDM系统的信道估计方法进行比较,仿真结果表明,所提的方法能够在使用较少的导频符号的同时得到更高的系统性能和信道估计精度.     

一种改进的MIMO-OFDM系统频域信道估计和跟踪方案

深入研究了MIMO-OFDM系统中的频域信道估计和跟踪算法．在分析比较了现有频域信道估计算法的基础上,提出了一种有效的改进频域信道估计和跟踪方案．该方案利用基于正交训练符号的算法求得初始信道估计值,利用信道估计和信号检测的联合迭代算法来跟踪随时间变化的信道参数．在典型的室内传输环境下对三种频域信道估计和跟踪方案进行了仿真比较,结果表明,本文所提方案在较低的迭代次数下就可以带来明显的性能改善．     

Aircraft parameter identification by the Gauss-Newton method in the frequency domain

A frequency-domain output-error method based on the Gauss-Newton minimization technique has been developed for the estimation of aircraft parameters from flight data. The method has been validated on simulated flight data. The effect of the intensity of measurement noise present in the flight data is studied and the method is shown to work satisfactorily even in the presence of high noise levels. Six different types of rudder and aileron control inputs have been used to generate the flight data; the analysis of such data is carried out to identify the suitable control input forms for the parameter estimation. Results are presented to show the effect of using the ‘packing theorem’ to increase the sparsely sampled frequency data; assigning a priori values to some of the weak parameters; and starting the iteration process with different initial values. Finally, a comparison of the method in the time domain and the frequency domain is presented to point out the relative merits of the latter approach.     

Analysis and design of output feedback control systems with actuator saturation

A dynamic output feedback controller design approach based on cone complementary linearisation procedure is proposed for linear time-invariant （LTI） systems with actuator saturation. First, the estimation of the domain of attraction is given. Then, a design method to find a larger estimation of the domain of attraction is presented. In the process of design, nonconvex conditions are obtained, so a cone complementary linearisation procedure is exploited to solve the nonconvex feasibility problem. Two examples are given to illustrate the efficiency of the design method.     

Multi-output parameter estimation of dynamic systems by output shapes

A multi-output method of parameter estimation is introduced for dynamic systems that relies on the shape attributes of model outputs. The shapes of outputs in this method are represented by the surfaces that are generated by continuous wavelet transforms (CWTs) of the outputs in the time-scale domain. Since the CWTs also enhance the delineation of outputs and their sensitivities to model parameters in the time-scale domain, regions in the time-scale plane can be identified wherein the sensitivity of the output with respect to one model parameter dominates all the others. This allows approximation of the prediction error in terms of individual model parameters in isolated regions of the time-scale domain, thus enabling parameter estimation based on a small set of wavelet coefficients. These isolated regions of the time-scale plane also reveal numerous transparencies to be exploited for parameter estimation. It is shown that by taking advantage of these transparencies, the robustness of parameter estimation can be improved. The results also indicate the potential for improved precision and faster convergence of the parameter estimates when shape attributes are used in place of the magnitude.     

基于插值和周期图法的高动态信号载波频偏粗估计

针对卫星通信系统中接收信号载波动态范围大、信噪比低造成的信号载波同步困难的问题进行了研究。基于联合插值和频域移位平均周期图法的载波频偏估计算法,通过对半符号周期频域移位平均周期图法中各并行支路输出的功率谱峰值波形进行双谱线插值,以进一步降低载波频偏变化率估计误差,进而改善原算法捕获概率。仿真结果显示,当比特信噪比为2.5 dB时,相比于半符号周期频域移位平均周期图法,该算法只增加了一次插值计算就可以实现将载波频偏变化率估计误差降低27%。在同等估计精度和参数设置下,相比于半符号周期频域移位平均周期图法和带补零频域移位评价周期图法,基于联合插值和周期图法的载波频偏粗估计算法可达到更高的捕获概率。     

Fault estimation observer design for a class of nonlinear multiagent systems in finite‐frequency domain

This paper focuses on the fault estimation observer design problem in the finite‐frequency domain for a class of Lipschitz nonlinear multiagent systems subject to system components or actuator fault. First, the relative output estimation error is defined based on the directed communication topology of multiagent systems, and an observer error system is obtained by connecting adaptive fault estimation observer and the state equation of the original system. Then, sufficient conditions for the existence of the fault estimation observer are obtained by using a generalized Kalman‐Yakubovich‐Popov lemma and properties of the matrix trace, which guarantee that the observer error system satisfies robustness performance in the finite‐frequency domain. Meanwhile, the pole assignment method is used to configure the poles of the observer error system in a certain area. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.     

Robust identification of first-order plus dead-time model from step response

In this paper, a simple yet robust identification method for a linear monotonic process, derived from a step test, is proposed. New linear regression equations are derived, from which the parameters of a first-order plus dead-time model can be obtained directly. No iterations in calculation are needed. The proposed method outperforms the existing estimation methods that use step-test responses. The estimation error is smaller in both the time domain and the frequency domain. Furthermore, the method is robust in the presence of large amounts of measurement noise. The effectiveness of the identification method has been demonstrated through a number of simulation examples and a real-time test.     

时域投影模型降阶方法的小样本误差估计

投影方法作为一类重要的模型降阶方法,其计算过程稳定,易于实现,但在理论上鲜有良好的时域误差估计结果．本文提出一种基于小样本估计过程的时域投影模型降阶误差估计方法．该方法首先将降阶过程中产生的误差分解为两部分,然后对各部分利用小样本估计方法进行估计．文中分别对线性和非线性输入输出系统进行小样本误差估计分析．此外,该方法能对线性系统的扰动问题进行分析,进一步的数值算例验证了该方法的有效性．     

Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian Estimation

This paper presents a new approximate Bayesian estimator for enhancing a noisy speech signal. The speech model is assumed to be a Gaussian mixture model (GMM) in the log-spectral domain. This is in contrast to most current models in frequency domain. Exact signal estimation is a computationally intractable problem. We derive three approximations to enhance the efficiency of signal estimation. The Gaussian approximation transforms the log-spectral domain GMM into the frequency domain using minimal Kullback-Leiber (KL)-divergency criterion. The frequency domain Laplace method computes the maximum a posteriori (MAP) estimator for the spectral amplitude. Correspondingly, the log-spectral domain Laplace method computes the MAP estimator for the log-spectral amplitude. Further, the gain and noise spectrum adaptation are implemented using the expectation-maximization (EM) algorithm within the GMM under Gaussian approximation. The proposed algorithms are evaluated by applying them to enhance the speeches corrupted by the speech-shaped noise (SSN). The experimental results demonstrate that the proposed algorithms offer improved signal-to-noise ratio, lower word recognition error rate, and less spectral distortion.     

An Identification Algorithm for Dynamic Systems with a Functional in the Frequency Domain

A parametric identification algorithm for dynamic systems is designed by the method maximum likelihood estimation in a time domain. Since the minimizing functional is formed in the frequency domain, the algorithm acquires new useful properties, mostly due to the suppression of disturbances through the choice of the working frequency ranges. The algorithm is modified such that time-shift disturbances of the recorded signal are suppressed.     

基于时空联合估计噪声子空间的MUSIC波束形成方法

针对在宽带短脉冲情况下频域MUSIC波束形成过程中噪声子空间估计不稳定的问题,提出了一种基于时空联合估计噪声子空间的MUSIC波束形成方法。该方法首先对线列阵接收数据构造时域复解析数据;然后根据增广数据构造方法和空间滑动的方法,在时域数据长度更短的情况下,稳定实现噪声子空间估计;最后根据估计出的噪声子空间含有的正交特性,通过单位矩阵与噪声特征向量相乘来得到相应波束。数值仿真和实测数据处理结果表明,相比频域MUSIC波束形成方法,该方法减少了稳定获取噪声子空间所需的快拍数,具有较好的稳定性和检测性能,提高了MUSIC波束形成在实际应用中的鲁棒性。     

CDMA信号的时频差高精度估计算法

针对多用户CDMA信号的时频域重叠特征,提出了一种新颖的时频差高精度估计方法。该方法结合扩频信号的捕获和解扩操作,以较短的信号样本和较低的计算量,仅两次时间-频率分维迭代实现了用户信号分离和时频差估计,再通过时域和频域内插进一步提高估计精度。仿真结果表明,与直接互模糊函数相关法相比,该方法能够有效提高CDMA信号时频差估计精度,降低计算量。     

基于声源时延估计的欠定盲分离方法

提出一种基于声源时延估计的二元时频掩蔽方法.通过三个接收信号实现多于多个语音源信号的欠定盲分离.利用语音信号的W-分离正交性,在时频域估计各个源信号到达接收阵列的相对时延序列;进而基于信号时延序列的估计,采用最大似然算法将时频域划分为与源信号个数相同的互不重叠的时频点集合,每个集合(近似)只包含一个源信号的所有时频分量;再通过二元时频掩蔽依次恢复出各集合所对应的源信号.该方法性能通过主观试听得到了验证,其分段信噪比增益至少为13 dB.较之欠定解混迭估计技术DUET,本文方法得到的分离信号与实际声源信号的相异度降低约3 dB.     

基于小波滤波器组的光流估计

为了解决光流估计时存在的孔径问题和时域混叠，在Bernard的理论基础上，给出了基于快速滤波器组的方法：小波函数在频域可以表示为滤波器组的乘积．所以时域的小波系数由傅里叶变换转换到频域。通过滤波器组快速求解。由于解析小波具有实小波所没有的优点．采用解析小波计算光流。文中给出该方法的结果。还给出了Horn-Schunck的正则化方法的结果。比较后可知，本文的方法能较好地对运动物体进行光流估计。     

基于PN序列的OFDM系统信道估计方法研究

文章介绍了OFDM系统中基于PN序列的信道估计技术,并对基于PN序列的时域迭代相关检测算法进行了改进,即在现有方法的基础上,把得到的信道冲激响应按固定的OFDM长度分块,并对每块符号进行补零、FFT,然后在时频二维平面进行三次样条插值得到每块符号中全部点的频率响应,与改进前及典型块状导频估计算法相比较,提高了估计精度。     

基于均匀圆阵的LFM信号DOA估计

针对为解决对雷达和通信中的线性调频信号源(LFM)定位的难题,为提高定位精度,提出了一种基于均匀圆阵的测向定位方法.方法通过分数傅立叶变换(FRFT)对LFM信号的能量聚焦特性,构造出一种新的FRFT域阵列数据模型;采用UCA-RB-MUSIC算法测向,通过模式激励法把阵元空间转换到实波束空间,对谱函数进行二维搜索,得到辐射源的方位角和俯仰角.通过理论推导和仿真验证,证明方法具有测向精度高、运算量小、360°全方位测向的优点.