Ergodicity of filtering process by vanishing discount approach

A new approach to study ergodicity of filtering processes is presented. It is based on the vanishing discount approach to discounted functional of filtering process. We show that limit superior of the Cesaro averages of the functionals is the same for all initial conditions from which the uniqueness of invariant measures of filtering processes follows. The approach is based on certain assumption for which we provide a sufficient condition using concavity arguments. In addition we show the existence of solutions to the Poisson equation corresponding to filtering process with concave functional. The assumptions are then extended to the controlled case and using similar concave arguments we obtain the existence of solutions to the Bellman equation corresponding to partially observed average cost per unit time problem.     

二维卡尔曼─中值混合自适应滤波

本文提出了能同时抑制加性噪声，脉冲噪声干扰和点扩展函数模糊，又能保护图象边缘及细节信息的新型滤波方法—“二维Kalman－Median混合自适应滤波”，并成功地应用于统计图象恢复，取得了满意的效果。     

Accurate Depth of Field Simulation in Real Time

We present a new post processing method of simulating depth of field based on accurate calculations of circles of confusion. Compared to previous work, our method derives actual scene depth information directly from the existing depth buffer, requires no specialized rendering passes, and allows easy integration into existing rendering applications. Our implementation uses an adaptive, two‐pass filter, producing a high quality depth of field effect that can be executed entirely on the GPU, taking advantage of the parallelism of modern graphics cards and permitting real time performance when applied to large numbers of pixels.     

Nonlinear suboptimal filtration of pseudorandom sequences

The critical importance of studies of alternative methods of representation and processing of signals constructed from pseudorandom sequences of maximal period is demonstrated. For the first time, it is proposed that a multidimensional nonlinear finite-difference representation of an arbitrary pseudorandom sequence be employed. A suboptimal algorithm for nonlinear discrete Kalman filtration of a pseudorandom sequence is obtained. A numerical example of filtration of a sequence formed on the basis of a given recurrence rule is considered and its efficiency is demonstrated.     

Author's reply to “Comments on ‘Performance evaluation of UKF-based nonlinear filtering”’

It is stated in the above-mentioned comment that the main result of the paper Xiong, Zhang, et al. [(2006). Performance evaluation of UKF-based nonlinear filtering. Automatica 42(2), 261-270] can be extended to a class of filters, such as the extended Kalman filter (EKF). As we show here, this belief can be justified in a rigorous way, even for the nonlinear stochastic system with a nonlinear measurement equation.     

多坐标系下目标跟踪的联合滤波

针对雷达目标观测和处理在不同的坐标系下完成，本文提出了联合滤波算法来跟踪机动目标。该算法以卡尔曼滤波器为基础，直角坐标系下和极坐标系下的算法相联合，不仅克服了两种坐标系下滤波算法的不足，而且对机动目标有很好的跟踪效果。仿真实验结果表明了该算法的有效性。     

MEMS惯性传感器ADIS16355在姿态测量中的应用

设计了基于微电子机械系统(Microelectro mechanical system,MEMS)惯性传感器集成模块ADIS16355的姿态测量系统。该姿态测量系统采用ADIS16355作为惯性测量单元,利用加速度计对重力向量的观测来修正陀螺给出的姿态信息,卡尔曼滤波实现传感器信息融合以计算运动载体的姿态角。介绍了ADIS16355的基本功能模块,阐述了两种传感器融合测量实时姿态角的方法并给出了卡尔曼滤波算法迭代过程。基于ARMv7架构的Cotex-M3微处理器设计了姿态测量系统硬件。采用AHRS500GA对该姿态测量系统性能进行了测量姿态角的验证实验。测试结果表明,该姿态测量系统能在动态条件下准确地测定运动物体实时姿态角,其误差一般在±1°左右。     

基于扩展卡尔曼滤波的测量系统数据分析

为消除误差和随机干扰对测量数据的影响。利用扩展卡尔曼滤波算法对测量数据进行处理,并提出基于扩展卡尔曼滤波算法的不可信点判断方法对测量数据进行野值剔除。两种方法结合运用,可以在保留数据特征的基础上,提高数据的精度,更好地反映测量目标的性能。     

应用代理系统在信息披露中的应用

提出了一种用开源软件对Web网站进行应用保护的方式,并通过研究,提出了修改程序的思路和方法,使得该程序可以更好地为应用系统服务,同时也使得代理程序不会成为应用程序和客户端之间额外的负担。     

基于卡尔曼滤波的电力虚假数据注入攻击检测方法

能源互联网的主体是基于状态估计下的电力系统。虚假数据注入攻击（FDIA）通过恶意篡改或注入电力数据,进而引发错误的状态估计结果。这种攻击方式存在引发大面积停电事故的风险,严重影响能源互联网的正常运行。在matpower 4.0中的IEEE-14节点系统上,利用以残差方程为基础的标准残差检测法和目标函数极值法,对FDIA进行了检测实验。提出了一种基于卡尔曼滤波的FDIA检测方法,并在MATLAB上进行了验证。实验结果表明,该方法可以在短时间内发现FDIA的发生。