多传感器多目标跟踪融合中的目标航迹包含了模糊信息，这种模糊信息可以用模糊隶属度函数来描述。
The target track in the multisensor multitarget tracking fusion contains the fuzzy information which was described by the fuzzy membership function.
该算法降低了多传感器多目标跟踪的复杂性和计算量，有效地解决了异类多传感器可用公共信息少的问题。
The presented algorithm can reduce computing complexity and solve the common information-lacking problem of heterogeneous sensors efficiently.
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。
Secondly, for multi-sensor multi-target tracking, data association is one of important problems, and is the precondition of data fusion.
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。
A time and space joint probabilistic data association algorithm is developed to solve the difficult problem of passive multisensor-multitarget 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。
The Nearest Near Joint Probabilistic Data Association(NNJPDA) is not used directly in multi-sensor multi-target tracking.
研究炮兵系统多传感器多目标定位和跟踪的建模方法。
A method for the multi target locating and tracking with the multi sensor in a field artillery system is studied.
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.
针对炮兵打击目标的特性和获取目标信息所采用的侦察设施，研究了多传感器多目标定位和跟踪问题。
Considering properties of targets and sensors used to detect targets, this paper addresses the multi sensor multi target locating and tracking in the artillery system.
研究炮兵系统多传感器多目标定位和跟踪的建模方法。
Considering properties of targets and sensors used to detect targets, this paper addresses the multi sensor multi target locating and tracking in the artillery system.
研究炮兵系统多传感器多目标定位和跟踪的建模方法。
Considering properties of targets and sensors used to detect targets, this paper addresses the multi sensor multi target locating and tracking in the artillery system.
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