一类快速的宽带分布源到达角估计算法

针对宽带分布源到达角估计问题,提出了一类快速的估计算法,即中频法、中值法和均值法。该类算法首先将阵列接收的宽带信号变换到频率域,然后对于每个频率形成阵列接收信号协方差阵,最后由该协方差阵的次对角线元素估计宽带分布源的到达角,其主要特点是避免了相位展开。仿真结果表明,在高信噪比和分布角不大时,中频法和中值法的性能几利相同;但在低信噪比时,中值法优于中频法。此外,均值法对分布角不敏感,且性能较优。     

Bayesian sequential state estimation for MIMO-OFDM systems

For the estimation of MIMO frequency selective channel, to mitigate the curse of dimensionality, a novel particle filtering scheme combined with time delay domain processing is proposed. In order to extract the time delay domain channel impulse response from the observed signal, the least-squares (LS) and minimum mean squared error (MMSE) criteria are discussed and the comparable performance of LS with MMSE for samplespaced channel is revealed. Incorporated the dynamical channel model, gradient particle fil...     

分布式小卫星雷达阵列误差估计与校正方法

当前星载测量仪器难以获得分布式小卫星SAR系统相干处理的阵元位置测量精度,为此提出了一种可以直接从杂波数据中估计阵列误差的算法,进而可以对阵列误差进行有效的校正.该算法充分利用分布式小卫星SAR系统接收回波数据的空-时-频特点,具有简单、收敛快、估计精度高等优点.最后利用仿真验证了该方法的有效性.     

Bayesian estimation for nonlinear stochastic hybrid systems with state dependent transitions

The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems.However,most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system,few literature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions.According to this problem,a new methodology which relaxes quite a restrictive assumption that the mode transition process must satisfy Markov properties is proposed.In this method,a general approach is presented to model the state dependent transitions,the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline.Then maximum a posterior estimation is obtained by using the Bayesian theory.The efficacy of the estimator is illustrated by a simulated example.     

多基阵分布式估计融合新方法

针对水下多基阵分布式估计融合问题,为了解决常规方法中存在的获取完全水下信道特性难度大、算法实现复杂度高以及占用大量通信资源的缺点,在分布式等判决门限估计融合方法的基础上,建立了水下多基阵分布式估计融合模型,提出了多基阵分布式不等门限估计融合方法。理论分析和仿真试验表明：新方法在目标参数估计精度以及抗噪等方面优于等门限估计融合方法;在基阵数目较大时,其估计性能与似然估计方法相当。这种方法考虑了水声信道通信带宽的限制,满足了实际分布式估计融合系统对于计算量小、复杂度低以及实时性强的要求,能够应用于水下目标探测领域。     

Performance evaluation for damping controllers of power systems based on multi-agent models

This paper proposes a multi-layer multi-agent model for the performance evaluation of power systems, which is different from the existing multi-agent ones. To describe the impact of the structure of the networked power system, the proposed model consists of three kinds of agents that form three layers: control agents such as the generators and associated controllers, information agents to exchange the information based on the wide area measurement system (WAMS) or transmit control signals to the power system stabilizers (PSSs), and network-node agents such as the generation nodes and load nodes connected with transmission lines. An optimal index is presented to evaluate the performance of damping controllers to the system's inter-area oscillation with respect to the information-layer topology. Then, the authors show that the inter-area information exchange is more powerful than the exchange within a given area to control the inter-area low frequency oscillation based on simulation analysis. This work was supported in part by the National Natural Science Foundation of China under Grants Nos. 50707035, 50595411, 60425307, 60221301, and 50607005, in part by the 111 project (B08013) and Program for Changjiang Scholars and Innovative Research Team in University (IRT0515) and in part by the Program for New Century Excellent Talents in University (NCET-05-0216).     

混杂系统粒子滤波混合状态估计及故障诊断算法

混杂系统同时包含连续动态特性和离散动态特性,并且两种动态相互作用,使其故障诊断变得更加困难。针对此问题,提出了一种混合系统粒子滤波混合状态估计及故障诊断算法,提高了现有方法的适用范围和诊断效率。针对混杂系统受控迁移、自治迁移和随机迁移等特点,首先利用随机混杂自动机对系统离散状态(包括故障)和连续状态进行统一建模,重点对现有基于扩展卡尔曼粒子滤波的连续估计算法进行改进,支持利用在线监测数据来估计混杂系统各类迁移产生的各种离散和连续状态,最后根据离散状态估计结果快速实现故障诊断。通过对典型非线性混杂系统的故障诊断,证明了该方法的有效性。     

CARMA模型多新息增广随机梯度参数估计算法的收敛性

将多新息辨识理论用于研究CARMA模型的参数估计问题。首先用估计残差来代替信息向量中的不可测噪声项,导出了CARMA模型的增广随机梯度算法,进一步把标量新息推广为新息向量,导出了相应的多新息增广随机梯度辨识算法,并利用鞅收敛定理分析了多新息增广随机梯度算法的收敛性。最后的仿真结果验证了该算法的有效性。     

低频共形阵的宽带波束域高分辨方位估计方法

针对共形布阵技术,提出了适用于低频共形基阵的宽带波束域高分辨方位估计方法。首先利用基于二阶锥规划的波束优化技术设计适用于低频共形基阵的宽带恒定束宽波束形成器,然后用设计好的波束形成器对基阵输出数据进行空域预滤波,使宽带信号的不同频率分量能无失真地通过,同时抑制旁瓣区的干扰,最后针对滤波后的多波束输出采用波束域高分辨方位估计方法估计目标方位。由于基于二阶锥规划技术设计恒定束宽波束形成器仅需要对主波束进行拟合,提高了设计精度,减小了聚焦误差,从而提高了方位估计的性能。计算机仿真和湖上实验数据处理结果验证了该方法能有效地估计出水下低频宽带目标声源的方位。     

Optimization-based particle filter for state and parameter estimation

In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.     

基于Schur-Hadamard积波束形成的相干分布式信源参数估计

对于由本地散射导致的分布式信源参数估计,根据分布式信源空同角度信号密度的共轭对称特性,将相干分布式信源的方向向量化简为点信源方向向量与实矩阵的schut-Hadamard积,提出了一种基于Schur-Hadamard积波束形成的相干分布式信源中心波达方向和角度扩散参数估计算法.由于在约束条件中考虑了角度扩散,算法具有一定的鲁棒性,适用于角度扩散较大的场舍.仿真实验表明,与MUSIC类算法DSPE相比,基于Schur-Hadamard积的波束形成参数估计算法具有更好的信噪比性能和参数估计精度,更适用于复杂的通信环境.     

UBSS and blind parameters estimation algorithms for synchronous orthogonal FH signals

By using the sparsity of frequency hopping（FH） signals,an underdetermined blind source separation（UBSS） algorithm is presented. Firstly, the short time Fourier transform（STFT） is performed on the mixed signals. Then, the mixing matrix, hopping frequencies, hopping instants and the hooping rate can be estimated by the K-means clustering algorithm. With the estimated mixing matrix, the directions of arrival（DOA） of source signals can be obtained. Then, the FH signals are sorted and the FH pattern is obtained. Finally, the shortest path algorithm is adopted to recover the time domain signals. Simulation results show that the correlation coefficient between the estimated FH signal and the source signal is above 0.9 when the signal-to-noise ratio（SNR） is higher than 0 d B and hopping parameters of multiple FH signals in the synchronous orthogonal FH network can be accurately estimated and sorted under the underdetermined conditions.     

基于二阶统计量的分布式信源二维波达方向估计

对于由本地散射导致的分布式信源二维波达方向估计,根据空间角度信号密度的共轭对称特性,首先将相干分布式信源方向向量化简为传统点信源方向向量与实向量的Schur Hadamard积,进而提出了一种基于Schur Hadamard积的相干分布式信源二维波达方向估计算法。该算法通过构造基于Schur Hadamard积的二阶统计量,可直接给出仰角和方位角的估计值。与传统谱峰搜索类算法和经典子空间类算法相比,无须谱峰搜索和任何特征值或奇异值分解,有效地降低了计算量;所利用的二阶统计量对噪声不敏感,具有较好的信噪比性能。仿真实验表明,该算法具有较好的参数估计精度,可有效解决复杂通信环境下相干分布式信源的二维波达方向估计问题。     

Constrained cooperative control design for distributed morphing wing systems

An efficient design method is proposed for the cooperative control problem of morphing wing systems with distributed structures and bounded control inputs. The multi-agent model of the distributed morphing wing system is established. The cooperative controllers with saturation constraints are presented. By introducing the concepts in consensus algorithms, the cooperative information links in the controllers are described by graphs, and the corresponding Laplacian matrix is defined. The design conditions of the cooperative controllers are proposed, in the form of linear matrix inequalities. For the case of undirected information links, the controller design conditions are simplified as algebraic inequalities, which highly reduce the computation cost. The designed controllers are implemented on a distributed morphing wing platform, and experiments are carried out. Simulation and experiment results show that the controllers can make all the actuating units in the morphing wing system cooperatively achieve the desired positions, which demonstrates the effectiveness of the proposed theory.     

分布式MIMO-OFDM系统中的时频同步

针对分布式多输入多输出〖CD*2〗正交频分复用系统,提出一种新的训练序列及时频同步方案。在定时同步方面,它首先利用训练序列的时域共轭对称性完成粗定时同步,在此基础上进一步通过接收信号与本地时域训练序列移动相关完成细定时同步;在频率同步方面,它首先在时域利用接收信号相位差估计小数倍频偏,然后在频域利用训练序列良好的自相关性估计整数倍频偏。该方案不仅能够同时估计出各收发天线对之间的定时偏移和频率偏移,而且估计性能良好。     

On state feedback and pole assignment of the second order coupled singular distributed parameter systems in Hilbert space

State feedback and pole assignment of the second order coupled singular distributed parameter systems are discussed via functional analysis and operator theory in Hilbert space, in which infinite many poles are changed. The solutions of the problem and the constructive expression of the solutions are given by the generalized inverse of bounded linear operator. This research is theoretically important for studying the pole assignment and stabilization of the singular distributed parameter systems.     

基于DCS的发射分集MIMO雷达参数估计

针对目标在多角度观测下的散射系数估计问题,研究了基于分布式压缩感知（distributed compressed sensing, DCS）的发射分集多输入多输出（multiple-input multiple-output, MIMO）雷达参数估计方法。在分析发射分集MIMO雷达信号模型的基础上,构建了其联合稀疏表示模型;在分析正交匹配追踪（orthogonal matching pursuit, OMP）算法实现结构的基础上,提出了一种新的基于迭代式正交匹配追踪的DCS算法。仿真结果表明该方法的估计精度高于DCS SOMP和幅度相位估计+Capon的算法,重构概率也高于DCS-SOMP算法。     

基于双基地频率和方位联合估计算法研究

提出一种基于双基地频率和方位联合估计的新算法,是基于UN-ESPRIT方法和两个阵列之间的互相关DOA矩阵法,称之为UN-DOAa-ESPRIT算法。该算法可以同时估计目标信号的频率和两个基地(即两个阵列天线)方位角。所估计的参数自动配对,不需要额外的配对运算,而且在不知道的相关噪声环境下同样可以有效地进行估计。数值仿真结果证明了算法的有效性。     

Reduced bit low power VLSI architectures for motion estimation

Low power and real time very large scale integration(VLSI) architectures of motion estimation(ME) algorithms for mobile devices and applications are presented.The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference(RBSAD) metric for calculating matching error and conversion to full resolution sum of absolute difference(SAD) metric whenever necessary.Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthesized using Xilinx Synthesis Tools(XST),where the ME designs based on reduced bit(RB) algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.     

广义双线性系统状态观测器的设计

针对输入受约束的广义双线性系统进行了研究,提出了采用极点配置的方法来设计广义双线性系统状态观测器,得到了广义双线性系统状态观测器存在的充分条件,保证了观测误差Lyapunov意义下渐近稳定。此外,给出了广义双线性系统状态观测器的设计方法的具体步骤,通过一个数值算例说明了设计方法的合理性和有效性。