Time and direction of arrival detection and filtering for imaging in strongly scattering random media

We study detection and imaging of small reflectors in heavy clutter, using an array of transducers that emits and receives sound waves. Heavy clutter means that multiple scattering of the waves in the heterogeneous host medium is strong and overwhelms the arrivals from the small reflectors. Building on the adaptive time-frequency filter of [Borcea et al, SIIMS 2011;4(3)], we propose a robust method for detecting the direction of arrival of the direct echoes from the small reflectors, and suppressing the unwanted clutter backscatter. This improves the resolution of imaging. We illustrate the performance of the method with realistic numerical simulations in a non-destructive testing setup.     

Multiresolutional Maneuvering Target Tracking Fusion Algorithm Based on Singular Sensor and Multipale Models

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滤紫外和红外光的荧光玻璃的研制及其应用

研制出了掺铈、钐的滤紫外和红外光的硼硅酸盐荧光玻璃，测试了该玻璃的吸收光谱和荧光谱，并用其做了固体激光器工作物质的紫外和红外滤光套，能使激光效率提高２５％－５０５，从而促进固体激光器的微型化和实用化。     

Unscented fuzzy-controlled current statistic model and adaptive filtering for tracking maneuvering targets

A novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. A fuzzy system allows the filter to tune the magnitude of maximum accelerations to adapt to different target maneuvers, and unscented transformation can effectively handle nonlinear system. A bearing-only tracking scenario simulation results show the proposed algorithm has a robust advantage over a wide range of maneuvers and overcomes the shortcoming of the traditional current statistic model and adaptive filtering algorithm.     

A Maximum Entropy Method for Particle Filtering

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.     

Digital total variation filtering as postprocessing for Chebyshev pseudospectral methods for conservation laws

Digital total variation filtering is analyzed as a fast, robust, post-processing method for accelerating the convergence of pseudospectral approximations that have been contaminated by Gibbs oscillations. The method, which originated in image processing, can be combined with spectral filters to quickly post-process large data sets with sharp resolution of discontinuities and with exponential accuracy away from the discontinuities.     

光学空间滤波过程的计算机仿真

提出了一种利用MATLAB软件并通过计算机仿真光学空间滤波实验过程的新方法.其特点是:既可以随意改变所设计滤波器的参量,又可以对输入图象进行振幅、相位或复合滤波,并且可实现傅里叶变换频谱中相位信息的提取、存储和利用,因而能够完成一般光学实验中往往难以实现的某些操作.并分别给出了网格滤波、低通、高通及相位滤波等仿真实验结果.这种仿真实验给光学滤波器的设计和图象处理带来很大方便,同时也为相关器件的设计提供了一条新的途径.     

动态系统最优滤波的可靠性

—本文以静态测量的可靠性理论为基础，研究了动态系统最优滤波的可靠性及其特性，以ＧＰＳ动态定位为例，对其可靠性指标进行了初步分析。动态系统的可靠性理论对于研究动态系统的粗差剔除、容错技术、可靠性分析等具有重要意义     

Galileo系统动态滤波的研究

提出一种Galileo动态定位滤波的方法。该方法从Galileo系统接收机输出的定位结果入手，将各种误差因素的影响等效为一个总误差，对Galileo系统接收机的机动载体加速度采用当前统计模型，利用线性卡尔曼滤波器进行动态定位数据的处理，并将次优加权自适应卡尔曼滤波算法应用到Galileo系统动态定位中。该模型简单，实时性好，滤波后定位精度得到提高。