航迹关联是航迹融合的前提和基础。
Tracks correction is the premise and basis of tracks fusion.
针对此问题，提出了一种异步航迹关联方法。
To address the problem, an asynchronous track-to-track association method is presented.
航迹关联是组网雷达系统数据融合中的一项关键技术。
The trace association is a key technology in data fusion of netted radar system.
利用航迹预测、航迹关联和航迹检测对目标进行跟踪。
Tracking prediction tracking correlation and tracking detection are used in the method for multiple maneuvering target tracking.
本文讨论的信息融合是针对雷达目标识别航迹关联问题。
This information fusion discussed in this paper aims at the problem of target track correlation of radar.
传统的目标航迹关联方法卡尔曼滤波法在实际应用时有局限性。
The traditional method of Kalman filter for passive sonar target track association is limited in practice.
新算法把航迹关联问题最终归结为假设检验，使算法的原理更严密。
Track-to-track correlation is viewed as a hypothesis test by the new algorithm which makes the theory more rigorous.
本文主要对数据融合系统中航迹关联和属性融合的算法进行了研究。
In this paper, the methods of track association and attribute fusion in data fusion system are studied.
航迹关联的难点体现在处理几种典型情况，即航迹分叉、合并、相交。
The typical cases of track association such as track furcation, combination and cross are the most difficult.
在序贯航迹关联算法的基础上提出了一种广义经典分配航迹关联算法。
Track correlation is the main problem in the distributed multisensor system. This paper presents a generalized classical assignment algorithm based on the sequential track correlation criteria.
在多节点分布式多传感器融合系统中，航迹关联问题可以化为多维分配问题。
In a multi-node distributed multisensor fusion system, the problem of track correlation can be transformed to a problem of multi-dimension assignment.
为了提高多传感器数据融合的精度，数据或航迹关联成为对目标跟踪滤波的关键。
To improve the precision of multisensor data fusion, data or track association becomes the key of target tracking filter.
在分布式多传感器系统中的多节点情况下，航迹关联问题可以转化为多维分配问题。
In a distributed multisensor system, the problem of track correlation can be transformed into the problem of multi-dimension assignment.
对于分布式多传感器融合多目标跟踪系统，提出一种序贯处理的航迹关联融合算法。
For distributed multi-sensor fusion multi-target tracking system, an efficient sequential track-to-track correlation and fusion algorithm is proposed.
在对三种情况的物理背景进行分析的基础上，对目前的航迹关联算法进行了修改和优化。
After analyzing the physical background of the three cases, the algorithms of track association were modified and optimized.
本文研究了量测噪声与系统噪声相关情况下同步多传感跟踪系统的航迹关联及融合技术。
The track association and fusion technique of synchronized multi-sensor tracking system in case of correlated noises is developed.
文中系统地研究了基于边扫描边跟踪系统的多目标跟踪数据处理的航迹关联及滤波与预测。
This paper studied systematically the track correlation and filter forecast based on data processing of multitar- get track while scan system.
论文正是围绕这一需求展开的，研究了雷达情报数据融合系统的误差校正和航迹关联问题。
The research work exactly focuses on this need in this paper. The concept, the meaning of this study and the development are introduced both in and abroad.
航迹关联是多传感器目标跟踪系统进行航迹融合的基础，是对目标进行连续跟踪的关键技术之一。
Track correlation is the basis of track fusion based on multisensor target tracking system, which is one of the key techniques for tracking the target continuous.
多路径数据融合过程包括多路径数据关联与航迹关联，航迹关联通常是在数据关联的基础上进行的。
Multipath data fusion is composed of multipath data association and multipath trajectory association, and usually the trajectory association is the subsequence of the data association.
异类传感器航迹关联是航迹融合中的一个难点，红外传感器与雷达的航迹关联是典型的异类传感器航迹关联。
Track association of heterogeneous sensors plays an important role in track fusion, and the track correlation of infrared sensor and radar is a typical correlation of heterogeneous sensors.
针对多传感器多目标航迹关联的特点，提出了将基于聚类分析的ISODATA算法应用于航迹关联的解决方法。
A method of track association based on ISODATA algorithm for clustering analysis is put forward according to the features of multi sensor multi target track association.
在分布式雷达网中，航迹关联的正确率直接影响到雷达网的跟踪精度，就此提出了一种基于曲线拟合的航迹关联方法。
The correctness of track correlation has a direct impact on the tracking precision of radar network in distributed radar network.
在具有较高稳定性、可靠性和易实现性的航迹融合系统中，航迹关联和航迹融合是主要研究内容，系统结构设计也围绕这两个核心展开。
Track fusion systems with high stability, reliability and easy implementation have track association and track fusion as their key contents which are the kernel of system architectural design.
针对通常的航迹关联融合结构存在多个中间级系统航迹、航迹号管理复杂等问题，提出了一种适用于多传感器航迹关联融合的处理结构。
A new processing structure is proposed to solve the problem of existence of several mid-level system tracks and the complexity of tracks 'label management.
该方法有效地应用了神经网络的泛化能力以及自组织自适应的学习功能，且通过对网络输入结点的设计，能够很好地解决复杂航迹关联问题。
This algorithm solves the problem of complex correlation by the node's design of neural network's input based on application of extensive ability effectively and effective study ability of itself.
在利用多帧图像进行目标提取时，针对多帧图像积累的有效性保证问题，采取了在积累前进行图像形态膨胀的方法，通过图像流法进行多帧图像航迹关联。
When using multi-frame image to extract target, image morphological dilation is used firstly to accumulate multi-frame image effectively and then associate the track with image flow method.
提出利用渐近分析理论研究多类传感器相关参数及其在时间域上参数方程的航迹参数关联问题。
Using the theory of asymptotic expansions to study the problem of track parameter association is firstly advanced.
提出利用渐近分析理论研究多类传感器相关参数及其在时间域上参数方程的航迹参数关联问题。
Using the theory of asymptotic expansions to study a problem of track parameter association is firstly advanced.
第二章介绍了航迹数据融合中使用的主要技术，包括：航迹滤波算法、多站条件下的滤波算法、多目标条件下的数据关联算法等。
In the second chapter, related technologies are presented. These are algorithms for track-filtering, filtering on condition of multisensor, data association on condition of multitarget and so on.
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