共查询到14条相似文献,搜索用时 140 毫秒
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应用现代时间序列分析方法,基于ARMA新息模型、白噪声估值器和观测预报器,对带白色观测噪声的多通道ARMA信号,在线性最小方差最优信息融合准则下,提出了统一的和通用的按矩阵加权、按标量加权和按对角阵加权的多传感器信息融合Wiener滤波器,可统一处理滤波、平滑和预报问题.提出了计算局部估计误差方差和协方差的公式,它们被用于计算最优加权.同单传感器情形相比,可提高滤波精度.一个目标跟踪仿真例子说明了其有效性,且说明了三种加权融合滤波器的精度无显著差异,因而利用按标量加权融合滤波器以轻微的精度损失提供一种快速融合估计算法,便于实时应用. 相似文献
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多通道ARMA信号信息融合Wiener滤波器 总被引:2,自引:0,他引:2
应用Kalman滤波方法,基于白噪声估计理论,在线性最小方差最优信息融合准则下,提出了多通道ARMA信号的两传感器信息融合稳态最优Wiener滤波器、平滑器和预报器;给出了最优加权阵和最小融合误差方差阵.与单传感器情形相比,可提高滤波精度.一个雷达跟踪系统的仿真例子说明了其有效性. 相似文献
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对于带未知局部预报误差互协方差的两传感器跟踪系统,通过协方差交叉融合方法,得到了协方差交叉融合稳态Kalman预报器,并用协方差椭圆的方法给出了其精度关系的几何解释。用相关方法证明了协方差交叉融合稳态Kalman预报器的精度高于每个局部稳态最优Kalman预报器,低于按矩阵加权融合稳态最优Kalman预报器。用一个Monte-Carlo仿真例子说明了协方差交叉融合稳态Kalman预报器的精度接近于稳态最优融合Kalman预报器。 相似文献
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对于带未知噪声统计和带具有相同右因子的观测阵的多传感器系统,应用加权最小二乘(WLS)法可得到一个等价的融合观测方程。该文应用现代时间序列分析方法,基于新息模型参数的在线辨识,可估计未知噪声方差,进而提出了自校正加权观测融合Kalman滤波器。在新息模型参数估计是一致的和观测数据是有界的假设下,该文证明了自校正Kalman滤波器收敛于当噪声统计已知时的全局最优融合Kalman滤波器,因而它具有渐近全局最优性。最后给出了一个4传感器跟踪系统的仿真例子并验证了其有效性。 相似文献
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For the multisensor multichannel autoregressive moving average (ARMA) signals with time-delayed measurements, a measurement transformation approach is presented, which transforms the equivalent state space model with measurement delays into the state space model without measurement delays, and then using the Kalman filtering method, under the linear minimum variance optimal weighted fusion rules, three distributed optimal fusion Wiener filters weighted by matrices, diagonal matrices and scalars are presented, respectively, which can handle the fused filtering, prediction and smoothing problems. They are locally optimal and globally suboptimal. The accuracy of the fuser is higher than that of each local signal estimator. In order to compute the optimal weights, the formulae of computing the cross-covariances among local signal estimation errors are given. A Monte Carlo simulation example for the three-sensor target tracking system with time-delayed measurements shows their effectiveness. 相似文献
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White noise deconvolution or input white noise estimation problem has important application backgrounds in oil seismic exploration, communication and signal processing. By the modern time series analysis method, based on the Auto-Regressive Moving Average (ARMA) innovation model, under the linear minimum variance optimal fusion rules, three optimal weighted fusion white noise deconvolution estimators are presented for the multisensor systems with time-delayed measurements and colored measurement noises. They can handle the input white noise fused filtering, prediction and smoothing problems. The accuracy of the fusers is higher than that of each local white noise estimator. In order to compute the optimal weights, the formula of computing the local estimation error cross-covariances is given. A Monte Carlo simulation example for the system with 3 sensors and the Bernoulli-Gaussian input white noise shows their effectiveness and performances. 相似文献
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For the multisensor system with correlated measurement noises and unknown noise sta-tistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cross-covariances is obtained. Further, a self-tuning weighted measurement fusion Kalman filter is presented, based on the Riccati equation. By the Dynamic Error System Analysis (DESA) method, it rigorously proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion steady-state Kalman filter in a realization or with probability one, so that it has asymptotic global optimality. A simulation example for a target tracking system with 3-sensor shows that the presented self-tuning measurement fusion Kalman fuser converges to the optimal steady-state measurement fusion Kalman fuser. 相似文献
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For the multi-sensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is obtained using the correlation method.Substituting it into the optimal weighted fusion steady-state white noise deconvolution estimator based on the Kalman filtering,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented.By the Dynamic Error System Analysis(DESA) method,it proved that the self-tunin... 相似文献