有色噪声中一维谐波频率估计的稳健迭代算法

本文通过构造基于观测信号的统计量,采用三步迭代（TSI）算法来估计乘性和加性有色噪声中一维谐波信号频率参数,得到了最终估计量的渐近分布,证明了估计的一致性。TSI算法通过引入周期图估计作为初估计,从谐波模型内在特性出发构造统计量,采用迭代方式逐步提高初估计精度,仅需三次迭代就能达到加性噪声情形下最小二乘估计（LSE）的关于样本的收敛速度。由于只需要三次迭代就可以达到收敛,所以算法的计算量比较少。另外相比较传统的迭代算法而言,TSI算法能保证每次迭代后都能够提高估计的精度,从而克服了传统的迭代算法收敛不够稳定不足。仿真实验证实了估计的一致性以及估计的渐近分布,而且在较大噪声情形下该迭代算法依然可行。最后,由于TSI算法具备小的计算量以及高的估计精度,因而十分适合作为一维谐波参数估计的在线算法。      

关于二维谐波的建模问题

本文研究了噪声中二维谐波的建模问题，得取了Ｐ分量二维谐波的仅有Ｐ个系数的二维特征多项式。     

频率、二维到达角和极化联合估计

在宽频段内多信号多参量联合估计已成为许多研究课题,例如,。未知辐射源识别,有效对消等等的重要研究内容,信号频率与二维到达角、二维到达角与极化的联合估计已开展研究,但信号频率二维到达角和极化联合估计的研究尚未见报导,本文提出了利用交叉偶极子平面阵和ＥＳＰＲＩＴ算法实现频率、二维到达角和极化联合估计的新方法,分析了算法结构,计算机模拟结果证实了算法的有效性。     

基于FFT的快速高精度正弦信号频率估计算法

提出了一种新的基于FFT的快速高精度正弦信号频率估计算法。通过分析Jacobsen算法和傅里叶系数插值迭代算法的性能,指出Jacobsen算法计算简单,精度不高;傅里叶系数插值迭代算法精度较高,但需要进行两次迭代,每次迭代均需计算两点的FFT系数,计算量较大。结合这两种算法,文中提出一种改进的高精度算法。该算法采用Jacobsen算法作为迭代初值,仅需进行一次迭代就能达到原迭代算法两次迭代的性能。仿真结果表明该算法在FFT信噪比门限以上全频段估计的均方根误差十分接近克拉美罗下限,具有较强的抗噪性能,且计算量较少,易于实时实现。     

单矢量水听器二维DOA和频率联合估计算法

基于单矢量水听器,利用时延数据构造两个阵形相同的子阵,运用LS-ESPRIT方法,对信号数据矩阵进行特征值分解,提取其特征值和相应的特征向量中包含的频率和角度信息,从而实现单频窄带信号的二维DOA和频率的联合估计。具有较好的估计精度,无需搜索过程并且能够实现三维参数的自动配对。使用MATLAB进行仿真,与基于单矢量水听器的波达方向矩阵法和基于声压阵的LS-ESPRIT方法进行比较,结果表明,该方法具有较好估计性能。     

基于遗传算法的二维谐波频率估计

针对高斯有色噪声背景下的二维谐波频率估计问题,本文利用二维四阶累积量对高斯噪声不敏感,却包含有二维谐波的频率与幅度信息,将该问题转化为一个多元函数的极值问题,然后提出了基于遗传算法的二维谐波信号参数估计算法.该算法可以直接估计出谐波的频率与振幅,并且不需要考虑频率的配对问题,使得估计过程得到了简化.仿真实验证明了算法的有效性.     

实时高精度频率估计算法

提出一种高精度频率估计算法，即在低信噪比（ＳＮＲ）下降短时直接中频采样数据分段，求其平均幅度谱粗测频率，再加权其相位精确估计信号的频率，以便获得较高的测频精度。估计误差接近Ｃｒａｍｅｒ－Ｒａｏ（ＣＲ）下界，并且能够有效地分离同时达到的多个信号。     

四元数在多个频率对共用同一个频率下的二维谐波恢复

针对二维谐波频率估计中的分维配对问题,本文首先对一般二维谐波信号模型进行变换,构造了符合四元数结构的新的信号模型.接着讨论了Hamilton四元数、三维超复数在二维谐波频率估计中的可能性.同时利用Hua的思想,根据上述模型利用特殊的四阶累积量切片并构造增广矩阵分析了有多个频率对共享同一个频率时的二维谐波频率估计问题.     

一种迭代正弦频率估计硬件实现研究

 本文提出了一种基于迭代算法的八通道滤波器组单频正弦信号频率估计方法,该算法的基本思想是利用频域重叠的多通道滤波器来实现大的频率估计范围,同时提高单通道内的信噪比;还对滤波抽取后的数据进行迭代,这样即使采用运算量最小的不加权线性预测算法也能实现高精度测频,并采用FPGA实现了该算法,最后数值仿真结果证实所提算法的优异性能.     

面阵二维角度估计的RELAX算法

针对常规二维波达方向估计的高分辨算法的运算量大和稳健性差,将基于均匀线阵的RE-LAX算法拓展到均匀面阵中,得到了多快拍二维角度估计的二维RELAX（2-DRELAX）算法。对于常见的单目标存在地面反射多径的情况,将2-DRELAX算法进行简化,提出了一种基于行列合成处理和RELAX算法测角的双迭代方法。该方法由某个初始的二维角度出发,首先进行行列合成处理,将面阵接收的数据矩阵合成为行、列天线接收的数据矢量,然后由RELAX算法分别估计方位角和俯仰角,最后由估计的二维角度更新行列合成因子并进行行列合成,得到更精确的二维角度估计,如此迭代直至得到的二维角度满足给定的精度要求。该方法收敛速度快,无需特征值分解和多维搜索,对相关信号不需要解相关处理,具有较高的测角精度和分辨力。     

A weighted iterative method for robust self-calibration

A robust self-calibration method is presented, which can efficiently discard the outliers based on a Weighted Iteration Method （WIM）. The method is an iterative process in which the projective reconstruction is obtained based on the weights of all the points, whereas the weights are defined in inverse proportion to the reciprocal of the re-projective errors. The weights of outliers trend to zero after several iterations, and the accurate projective reconstruction is determined. The location of the absolute conic and the camera intrinsic parameters are obtained after the projective reconstruction. The theory and experiments with both simulate and real data demonstrate that the proposed method is very efficient and robust.     

A robust iterative method for Born inversion

We present a robust iterative method to solve the inverse scattering problem in cases where the Born approximation is valid. We formulate this linearized inverse problem in terms of the unknown material contrast and the unknown contrast sources and we solve the problem by minimizing a cost functional consisting of two terms. The first term represents the differences between the actual data and the modeled data, while the second term represents the misfit in the constitutive relations between the contrast sources and the incident fields. In each iteration, the contrast sources and the contrast are reconstructed alternatingly, using subsequently a conjugate gradient step for the contrast source updates and a direct inversion of a diagonal matrix for the contrast. A further regularization with a multiplicative regularization factor is discussed. In this regularization procedure the relative variation of the contrast is minimized as well. As a test case we consider the two-dimensional (2-D) transverse magnetic polarization problem. Synthetic numerical examples are presented in order to compare the presented algorithm to the traditional Born algorithm. Results with respect to the inversion of experimental data are presented as well. In addition, some inversion results for the subsurface sensing problem, both in two and three dimensions, are presented.     

Application of robust iterative learning algorithm in motion control system

Robustness issue is considered to be one of the major concerns in application of the iterative learning control in motion control systems. The robustness in servo systems is related to parameter uncertainties and noise accumulation. In this paper, both parameter uncertainties and noise are considered in derivation of the error dynamic equation of the ILC algorithm. Based on the error dynamics, the H_∞ framework is utilized to design the robust learning controller. An optimization design process in selecting the proper learning gain and determining the learning function is proposed to ensure that both tracking performance and convergence condition are achieved. Simulations and experiments are conducted to validate the robust learning algorithm which can be applied efficiently to machine tools with the payload varying from 0 to 20 kg. The experimental results demonstrate that the proposed method improves the tracking and contouring performances significantly when performing a complex NURBS curve on a three-axis milling machine.     

T矩阵递推算法用于二维混合目标RCS计算

利用递推算法计算任意形状二维导体加介质体目标的电磁散射。建立导体部分单独存在时的T矩阵，对于内谐振频率点上生成的病态矩阵用奇异值分解方法解决，用广义递推算法求出有耗介质单体T矩阵。然后采用二体散射的方法求得总散射场。计算结果表明了该方法的正确性。     

一种快速二维相关干涉仪测向算法

针对宽带信道化测向处理中传统二维相关干涉仪测向算法计算量过大的缺点,提出了一种基于引导基线的快速相关干涉仪算法.在阵列中选定引导基线,由引导基线的相位差信息计算出一组可能的来波角度信息;在测向处理时,仅对引导基线确定的角度进行相关度计算.快速算法将传统相关干涉仪中的二维相关峰搜索减小为仅对一个由模糊角度组成的点集进行搜索,计算量不到传统方法的百分之一,且测向性能与传统方法相当.试验验证了该算法的有效性.     

Performance tuning of robust motion controllers for high-accuracy positioning systems

This paper presents a structural design method of robust motion controllers for high-accuracy positioning systems, which makes it possible to tune the performance of the whole closed-loop system systematically. First, a stabilizing control input is designed based on Lyapunov redesign for the system in the presence of uncertainty and disturbance. And adopting the internal model following control, robust internal-loop compensator (RIC) is proposed. By using the structural characteristics of the RIC, disturbance attenuation properties and the performance of the closed-loop system determined by the variation of controller gains are analyzed. Next, in order to design a robust motion controller for a high performance positioning system, dual RIC structure is proposed and it is shown that if the synthesis of the robust motion control law is performed in the RIC framework, the robust property of RIC can be naturally implanted in the feedback controller. The proposed structural design of robust motion controller provides a systematic approach to the problem of robust stability and performance requirement in the face of uncertainty. Furthermore, by allowing the tradeoffs between robust stability and performance to be quantified in a simple fashion, it can illuminate systematic design procedure of the robust motion controllers. Finally, the proposed method is verified through simulation and the performance is evaluated by experiments using a high-accuracy positioning system.     

A high-accuracy realization of the Yee algorithm using non-standardfinite differences

New nonstandard second-order finite differences (FD's) are introduced, which when substituted into the Yee algorithm, reduce the solution error by a factor of 10^-4 on a coarse computational grid. Using λ/h (grid spacings per wavelength)=8, one achieves the same accuracy as the standard Yee algorithm does at λ/h=1140. In addition, greater algorithmic stability allows a reduction in the number of iterations needed to solve a problem     

A robust method for estimating respiratory flow using tracheal sounds entropy

The relationship between respiratory sounds and flow is of great interest for researchers and physicians due to its diagnostic potentials. Due to difficulties and inaccuracy of most of the flow measurement techniques, several researchers have attempted to estimate flow from respiratory sounds. However, all of the proposed methods heavily depend on the availability of different rates of flow for calibrating the model, which makes their use limited by a large degree. In this paper, a robust and novel method for estimating flow using entropy of the band pass filtered tracheal sounds is proposed. The proposed method is novel in terms of being independent of the flow rate chosen for calibration; it requires only one breath for calibration and can estimate any flow rate even out of the range of calibration flow. After removing the effects of heart sounds (which distort the low-frequency components of tracheal sounds) on the calculated entropy of the tracheal sounds, the performance of the method at different frequency ranges were investigated. Also, the performance of the proposed method was tested using 6 different segment sizes for entropy calculation and the best segment sizes during inspiration and expiration were found. The method was tested on data of 10 healthy subjects at five different flow rates. The overall estimation error was found to be 8.3 +/- 2.8% and 9.6 +/- 2.8% for inspiration and expiration phases, respectively.     

Statistical iterative scheme for estimating atmospheric relativehumidity profiles

Estimation of atmospheric relative humidity profiles using passive remote sensing techniques is difficult when the temperature profile is not well known, and such retrievals approach singularity when the atmosphere is nearly isothermal. A retrieval method that is more robust near isothermal regions and temperature inversions is described. Its robust character results from an iterative combination of statistical methods based on a priori data, which stabilize the effects of any singularities, and physical methods that reflect the nonlinear character of the equation of radiative transfer and the dependence of measurements on uncertain surface reflectivities and temperature profiles. This method can be used to interpret data from meteorological satellites. It was tested extensively using simulated clear-sky microwave observations from space at 89 GHz, 166 GHz, and three frequencies near the 183-GHz water vapor resonance and the 60-GHz oxygen band, which is sensitive to the atmospheric temperature profile. Humidity profiles from the tropical, midlatitude, and arctic regions were retrieved. Relative humidity profiles retrieved using the statistical iterative method typically had errors between 5 and 10% in the 300-1000 mbar pressure region. These errors were somewhat less in the tropics and greater in the polar regions, and represented significantly better performances than a linear statistical retrieval method