Multi-sensor data fusion has two main classes: estimation fusion, decision fusion.
多传感器数据融合分两大类：估计融合，决策融合。
In estimation fusion, three fusion architectures are considered: centralized, distributed, and hybrid.
在估计融合问题中，讨论了估计融合的中心式，分布式和混合融合结构；
This paper presents the effect of the common process noise on track statistical distance and performance of state estimation fusion.
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。
The method of state estimation is discussed, when radars have different observation dimension in one distributed data fusion system with feedback.
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。
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.
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。
System error estimation for active radar and passive radar is the key for realizing high precision Information fusion of passive radar and active radar.
有源雷达和无源雷达系统误差估计是实现有源无源雷达信息高精度融合的关键环节之一。
This dissertation points out the most pivotal problems in data fusion, i. e., data association, state estimation and target recognition, which are investigated in depth.
本文指出了数据融合中最为关键的几个问题——数据关联、状态估计和目标识别并围绕它们进行了深入的研究。
Its track fusion process includes states and attributes estimation of low levels, it also includes battlefields situation and threaten evaluation of high levels.
其航迹融合过程包括低层次上的状态和属性估计及高层次上的战场态势和威胁评估。
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。
Multi-sensor information fusion state estimation problem for descriptor discrete-time stochastic linear systems is studied.
研究了广义离散随机线性系统的多传感器信息融合状态估计问题。
This paper presents a new method of multisensor data fusion for measuring the temperature based on parameter estimation, and gives the data fusion algorithm.
本文提出了一种基于多传感器参数估计数据融合的热处理炉温度测量方法，给出数据融合算法。
The problem of multi-sensor information fusion state estimation for descriptor discrete-time stochastic linear systems is considered.
考虑了广义离散随机线性系统的多传感器信息融合状态估计问题。
By applying an emergent random weighting estimation method to multi-sensor data fusion, a random weighting data fusion method of multi-source information disposing was proposed in this paper.
将一种新兴的随机加权估计方法应用于多传感器数据融合，提出了一种将多源信息综合处理的随机加权数据融合方法。
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.
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。
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.
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 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.
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。
For this special multisensor system, distributed optimal fusion algorithm is received by avoiding computing correlated estimation covariance based on the matrix operation.
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。
The exchange of two nonlinear Kalman filters was used to improve the fusion accuracy in the state estimation.
在作状态估计时，采用两组非线性卡尔曼滤波切换提高融合精度。
A joint data association and bias estimation method is proposed to handle the negative effect of individual radar bias to track association and fusion in radar networks for target tracking.
针对雷达组网目标跟踪系统中，单雷达系统偏差严重影响多雷达航迹数据关联及融合跟踪质量的问题，提出了一种联合数据关联与系统偏差估计的方法。
The application of Wavelet in dynamic estimation and data fusion is introduced in this paper; an optimal real-time multiscale estimation and fusion algorithm for dynamic system is given.
介绍了小波变换在动态估计和数据融合中的应用，给出了一种实时的最优动态多尺度估计和融合算法。
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.
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。
On the other hand, state estimation plays an important role in systems and control theory, signal processing and information fusion.
另一方面，状态估计问题在系统与控制理论、信号处理与信息融合中有很重要的应用。
Based on the linear unbiased minimum variance estimation theory, an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed.
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。
An information fusion model for identification, diagnosis, estimation and forecast of formation damage using the data fusion technique and the uncertainty decision theory was established.
应用信息融合技术与不确定性决策理论，构建了对油气储层损害进行识别、诊断、评价和预测的信息融合模型。
This paper first introduced the kalman filter, to all sorts of navigation data information fusion, thus constituting navigation system, in order to get the optimal estimation system state.
本文首先介绍了卡尔曼滤波器，对各种导航数据进行信息融合，从而组成导航系统，以获取系统状态的最优估计。
The filtering methods based on information fusion estimation in linear or nonlinear systems was presented for the filtering problem in discrete dynamic stochastic system.
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.
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。
应用推荐