Adaptively robust filtering with classified adaptive factors

The key problems in applying the adaptively robust filtering to navigation are to establish an equivalent weight matrix for the measurements and a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information to the state parameter estimates. In this paper, an adaptively robust filtering with classified adaptive factors was proposed, based on the principles of the adaptively robust filtering and bi-factor robust estimation for correlated observations. According to the constant velocity model of Kalman filtering, the state parameter vector was divided into two groups, namely position and velocity. The estimator of the adaptively robust filtering with classified adaptive factors was derived, and the calculation expressions of the classified adaptive factors were presented. Test results show that the adaptively robust filtering with classified adaptive factors is not only robust in controlling the measurement outliers and the kinematic state disturbing but also reasonable in balancing the contributions of the predicted position and velocity, respectively, and its filtering accuracy is superior to the adaptively robust filter with single adaptive factor based on the discrepancy of the predicted position or the predicted velocity.     

基于函数连接型神经网络的非线性滤波

提出了一种基于函数连接型神经网络(FLNN)的非线性滤波解决方案,比较了线性滤波器和FLNN神经网络在非线性滤波中的性能差异。应用MATLAB针对伴有随机噪声的信号进行了仿真滤波试验,证明了该理论的可行性。     

一种基于位移概率矩阵的目标跟踪方法

针对非刚体目标跟踪问题,提出了一种采用快速块运动估计算法SSC-APDS计算位移概率矩阵的新方法.由SSC-APDS首先计算出可能位移的误差和(SAE)曲面,并据此形成位移概率矩阵.在此基础上,采用一个基于位移概率矩阵的时间滤波器来完成对目标特征块的运动分析.最后根据各特征块的运动情况,得到目标的整体运动.实验证明该跟踪方法不仅具有很好的鲁棒性,且计算效率高,在以视频网格为平台的视频监控系统中跟踪效果好.     

不等式的证明

不等式的证明方法很多 ,本文给出了几种常用方法 ,通过这些方法 ,可以比较简洁 ,快速的解决一些不等式证明问题     

Second order asymptotic comparison of estimators of a common parameter in the double exponential case

Summary The problem to estimate a common parameter for the pooled sample from the double exponential distributions is discussed in the presence of nuisance parameters. The maximum likelihood estimator, a weighted median, a weighted mean and others are asymptotically compared up to the second order, i.e. the ordern ^−1/2 with the asymptotic expansions of their distributions. University of Electro-communications     

Robust Parameter Estimation for Stochastic Differential Equations

We consider the estimation of parameters in stochastic differential equations (SDEs). The problem is treated in the setting of nonlinear filtering theory with a degenerate diffusion matrix. A robust stochastic Feynman–Kac representation for solutions of SDEs of Zakai-type is derived. It is verified that these solutions are conditional densities for the conditional measures defined by degenerate filtering problems. We show that the corresponding estimator for the parameters is robust in the following sense: It depends continuously on both the measurement path and on the intensity of the measurement noise. An algorithm based on a Monte-Carlo approach is given for the practical application of the estimator, and numerical results are reported. Mathematics Subject Classifications (2000) Primary: 62M05, 62M20; secondary: 62F15.     

Smoothness of Nonlinear Median-Interpolation Subdivision

We give a refined analysis of the Hölder regularity for the limit functions arising from a nonlinear pyramid algorithm for robust removal of non-Gaussian noise proposed by Donoho and Yu [6,7,17]. The synthesis part of this algorithm can be interpreted as a nonlinear triadic subdivision scheme where new points are inserted based on local quadratic polynomial median interpolation and imputation. We introduce the analogon of the Donoho–Yu scheme for dyadic refinement, and show that its limit functions are in C for >log₄(128/31)=1.0229.... In the triadic case, we improve the lower bound of >log₂(135/121)=0.0997... previously obtained in [6] to >log₃(135/53)=0.8510.... These lower bounds are relatively close to the anticipated upper bounds of log₂(16/7)=1.1982... in the dyadic, respectivly 1 in the triadic cases, and have been obtained by deriving recursive inequalities for the norm of second rather than first order differences of the sequences arising in the subdivision process.     

地铁供电系统有源滤波协同无功补偿装置的研究

随着城市轨道交通的迅速发展,地铁供电系统动力照明负荷、变频设备的使用持续增多,导致无功功率和谐波问题日益严重。提出一种利用0.4 kV侧设置的有源滤波装置协同电抗器进行35 kV系统无功补偿的新方法。在地铁供电系统无功补偿领域内,首次将两者结合,探索出既节省成本,又能满足地铁供电系统功率因数要求的新无功补偿方式。     

自适应卡尔曼滤波方法及其在容错组合导航系统的系统级故障检测中的应用

提出了采用自适应加权和卡尔曼滤波相结合的自适应滤波方法进行组合导航系统极故障检测的新思路。该方法不仅可以判断出故障是否出现,而且可以对故障量的值进行跟踪估计,在估计的同时可以判断故障值出现在哪一个量测通道中。SINS／GPS组合导航系统故障检测和隔离的系统仿真结果验证了本算法的有效性。