Data association is one of basic questions in data fusion processing.
数据关联是数据融合处理中基本的问题之一。
This paper brings out a new Joint Probability Data Association Algorithm.
提出了一种新的联合概率数据互联的算法。
The other estimates target state without explicit use of a data association algorithm.
另一类在估计目标状态时并没有利用数据融合。
The performance of probability data association (PDA) can be improved by this algorithm.
该算法提高了概率数据关联(PDA)算法的性能。
Data association is an important step in ambiguity resolution in multiple target environment.
数据关联是多目标解模糊的关键一步。
Data association method in multi sensor multi maneuver target tracking is simultaneously argued.
同时还研究了多传感器跟踪多机动目标过程中的数据关联方法。
Multiple Target Tracking system concludes data association algorithm and data filtering algorithm.
多目标跟踪系统包含了数据互连算法和数据滤波算法。
Data alignment is a basic work to data association, target tracking and identification of data fusion system.
数据对准是数据融合系统中相关、跟踪和识别等功能的基础。
Afterwards a fast algorithm for track initiation and data association in multiple target tracking is obtained.
给出了多目标跟踪起始和数据关联的快速算法。
Tracking initiation and data association are key techniques of multi-target passive tracking by single observer.
跟踪起始与数据关联是机动多目标单站无源跟踪的关键技术。
Considering spatial characteristic of data association, the nearest neighbor algorithm is investigated in detail.
考虑到空间数据关联的特点，作者对空间最近邻居定位算法进行了详细的研究。
A new fast algorithm is presented to solve the data association in multitarget tracking in cluttered environment.
提出了一种新的多目标跟踪快速数据关联算法。
To solve the problem of data association in maneuvering target tracking, a new method of data association is proposed.
为解决机动目标跟踪过程中的数据互联问题，该文提出了一种数据互联新方法。
Two kinds of data association conditions - homogeneous sensors and heterogeneous sensors are reseaerched in this thesis.
研究了两种情况的数据关联-同类传感器和异类传感器。
The Nearest Near Joint Probabilistic Data Association(NNJPDA) is not used directly in multi-sensor multi-target tracking.
传统的最邻近联合概率数据关联算法（NNJPDA）不能直接用于多传感器对多目标的跟踪。
Secondly, for multi-sensor multi-target tracking, data association is one of important problems, and is the precondition of data fusion.
其次，对于多传感器多目标跟踪问题，数据关联是其中一项重要问题，也是实现多传感器数据融合的前提。
For the data association problem in the passive sensor system, a new fuzzy-probability weighting data association algorithm was proposed.
针对被动传感器系统中的数据关联问题，提出了一种新的被动传感器系统模糊-概率双加权数据关联算法。
Otherwise, fuzzy reasoning method is used for data association. The arithmetic is mainly used while some targets fall in one tracking door.
另外，文中还采用模糊推理方法进行数据关联，此算法主要用于多个候选目标落入同一跟踪门时的情况。
Compared with traditional arithmetic of data association, it's operation speed is faster, and it is better fit for engineering application.
它与传统的联合数据关联和多假设法相比，运算速度快，适于工程应用。
Just in case you didn't know, OBEX is not a native protocol of Bluetooth, but was actually created by the designers of Infrared Data Association.
也许您不知道，OBEX并不是蓝牙本身的协议，实际是由无线数据协会创建的。
Dynamic methods employ the rule of movement of real target to erase ghosts. An applying of joint probability data association (JPDA) is presented.
动态方法利用真实目标的运动规律去除虚假目标，本文介绍了联合概率数据关联(JPDA)在此的应用。
The practical results show that the method in this paper is suitable to deal with data association of week clutters and sparse targets environment.
实际应用表明，本文数据关联模型以及差额法适合于处理背景杂波不太强和目标不太密集情况下的异地多传感器数据关联问题。
The common data association algorithms include nearest neighbor algorithm, probabilistic data association and joint probabilistic data association.
常用的数据互联方式包括最远邻数据联解闭解、概率数据互联和解开概率数据互联。
A time and space joint probabilistic data association algorithm is developed to solve the difficult problem of passive multisensor-multitarget tracking.
还提出了一种适合于实际工程应用的时空联合数据概率关摘要联算法，该算法解决了无源多传感器多目标跟踪的难题。
The paper presents e-commerce website based on data association rules, and in detail elaborates system design targets, overall structure and functional modules.
本文研究了一种基于数据关联规则的电子商务网站，并详细阐述了系统的设计目标，总体架构及各功能模块的详细设计。
Computer simulation results show that the ACDA could get higher correct data association rate and lower computational complexity with the high speed small target.
实验结果表明，该方法对应用在机动性较弱的高速小目标数据关联时能够获得较高的正确关联率，且运行时间较短。
For the inconsistency problem of heterogeneous sensors' measurement Spaces, a new data association (da) algorithm based on fuzzy clustering algorithm is presented.
针对异类传感器观测空间不一致的问题，提出了基于模糊聚类的异类多传感器数据关联算法。
The similarity measurement algorithm is a data association method for assigning the local tracks based on the pattern similarity, which has a fine association effect.
相似性测度算法是根据航迹模式完成各局部航迹分配的关联方法，关联效果较好。
The probabilistic data association algorithm is applied in the spatial domain multi resolution frame and target tracking is implemented at the coarse resolution level.
这个算法在空间多分辨率框架下应用概率数据互联算法，在粗分辨率上实现模糊目标跟踪。
The probabilistic data association algorithm is applied in the spatial domain multi resolution frame and target tracking is implemented at the coarse resolution level.
这个算法在空间多分辨率框架下应用概率数据互联算法，在粗分辨率上实现模糊目标跟踪。
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