同单传感器情况相比，可提高融合估计精度。
Compared to the single sensor case, the accuracy of fused estimation is improved.
也就是说，融合估计只由测量值的质量来估计。
That is, the combined estimate is weighted by the quality of the measurements.
本文研究动态系统过程噪声对航迹统计距离和状态融合估计性能的影响。
This paper presents the effect of the common process noise on track statistical distance and performance of state estimation fusion.
雷达和红外数据共同作为神经网络的输入，输出为目标的最优融合估计。
The processed data are transmitted to the central neural network where a fused estimation of target is formed.
本文主要针对带乘性噪声系统的多传感器最优滤波融合估计算法作进一步研究。
The optimal filtering fusion algorithms for systems with multiplicative noises under multi-sensor observation are mainly researched in this dissertation.
基于非线性信息融合估计定理，推导出一种计算简单的迭代型非线性滤波方法。
Based on the nonlinear information fusion theorem, an iterative fusion estimation method with small computation cost was derived.
与各局部估计以及状态向量按标量加权融合估计相比，分量融合滤波具有更高的精度。
Compared with all local filters and the fusion filter weighted by scalars for the state vector, the component fusion filter weighted by scalars has higher precision.
文中比较了三种融合估计的精度和计算负担，可应用于信息融合状态或信号最优估计。
Their precision and computational burdens are compared. They can be applied into optimal information fusion estimation for the states or signals.
针对离散随机动态系统的滤波问题，提出了基于信息融合估计的线性和非线性滤波方法。
The filtering methods based on information fusion estimation in linear or nonlinear systems was presented for the filtering problem in discrete dynamic stochastic system.
数据融合方法采用经典的自适应加权融合估计算法，配合智能判别技术，增强了火灾特征识别的可靠性。
Combined with intelligent recognition technology, data fusion technology adopts the classical self-adapting weighting fusion algorithm to increase the reliability of fire characteristics recognition.
在初步分离结果的基础上，利用多模型融合滤波算法对故障进行精确定位并得到状态和故障的融合估计。
Then based on the primary isolation result, the fault is accurately located by the multiple-model fusion filtering algorithm, and the fused state and fault estimates are obtained as well.
本文主要针对多通道带乘性噪声系统的观测噪声最优估计算法和状态最优融合估计算法展开进一步研究。
The optimal estimation algorithm of measurement noise and the optimal state fusion algorithm for multi-channel system with multiplicative noises are mainly researched in this dissertation.
在这类特殊的多传感器系统中，本文通过矩阵运算消除相关估计方差，得到了最优分布式融合估计算法。
For this special multisensor system, distributed optimal fusion algorithm is received by avoiding computing correlated estimation covariance based on the matrix operation.
将强跟踪滤波理论与多传感器数据融合估计方法相结合，提出基于强跟踪滤波器的多传感器数据融合估计新算法。
By combining the strong tracking filtering theory with data fusion estimation approaches, we put forward a new fusion estimation algorithm of multi sensor based on strong tracking filter.
该算法釆用线状掩模窗口和最优融合估计方法，有效地增强了边缘保持能力和去噪能力，克服了边缘保持滤波器存在的缺陷。
By using linear mask and the optimal fusion estimation, this algorithm improves the ability of edge keeping and denoising effectively, overcomes the disadvantages of the edge keeping filter.
本文对某些传感器出现通信故障的多传感器动态系统进行了研究，通过改进现有的系统框架，提出了一种新的融合估计算法。
Fault diagnosis process based on the Ontology was elaborated, and then the fault knowledge expression and the fault diagnosis algorithm based on the Ontology were put forward.
基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
研究了全局最优融合估计算法。研究结果表明：全局最优估计的误差要小于局部估计的误差，即全局估计优于每一个局部估计。
In this paper, the algorithms of overall situafion optimum fusion estimate is studied. The study results prove that overall situafion optimum estimate is superior to part part estimate.
基于多传感器单模型动态系统的多尺度估计理论，研究了不同尺度上拥有不同统计特性的多尺度融合算法及多尺度分布式融合估计算法。
Basing multiscale estimation theory of multi-sensors and single-model of dynamic system, the multiscale fuse algorithm and multiscale distribute fuse algorithm were studied respectively.
本文的研究内容为多传感器信息融合理论中的状态融合估计理论，主要针对精确估计的实际应用中，状态融合估计理论存在的一些问题提出了解决方法。
This dissertation considers state fusion estimation of multisensor information fusion theory. The main work of here is to solve the problems when fusion estimation theory is applied in practice.
论述了带反馈分布式信息融合系统中传感器观测维数不同时的状态估计方法。
The method of state estimation is discussed, when radars have different observation dimension in one distributed data fusion system with feedback.
该算法能充分利用纸机系统的各状态之间的强耦合性，利用纸机系统的可测量信息，融合多个测量输出估计纸机的某一个状态。
The algorithm can fully utilize the coupling performance between different states and the measurable information and fuse several outputs to estimate one state of paper machine.
该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
基于线性无偏最小方差估计理论，提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。
Based on linear unbiased minimum variance estimation theory, a fusion algorithm which fused the state vector of nonlinear systems with dissimilar sensors with arbitrary correlated noises is developed.
移动机器人的导航子系统利用卡尔曼滤波器，融合由视觉系统与由里程计获得的位置估计值。
The navigation subsystem of the mobile robot fuses the position estimation obtained by a vision system with the position estimated by odometry using a Kalman filter.
给出一种基于噪声方差估计的稳健融合算法。
A robust fusion algorithm based on noise variance estimation is presented.
给出一种基于噪声方差估计的稳健融合算法。
A robust fusion algorithm based on noise variance estimation is presented.
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