In the background of multi-sensor data fusion, three key technologies are discussed in this thesis focused on multi-sensor multi-target tracking, including maneuvering target state estimation, data association and special situation processing.
本文以多传感器数据融合为背景，研究了多目标跟踪技术三方面的关键技术：机动目标状态估计、数据关联以及特殊情况处理。
参考来源 - 多传感器数据融合中多目标跟踪关键技术研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Based on the results of target state estimation error analyzing of this algorithm, this paper gives out an error compensation method.
根据对该算法的目标状态估计误差分析结果，文中给出了一种误差补偿方法。
Experimental results demonstrate that it is sufficient to only use the information on nodes with higher local SNR for target state estimation.
实验结果表明，它是足够的，只使用节点上的信息具有较高的本地SNR为目标状态估计。
For the problem of loss of target signal during target tracking in passive seeker, a new method is presented for anti-loss of target signal based on target state estimation.
围绕被动导引头跟踪过程中目标辐射源信号丢失的问题，提出一种基于目标状态估计的抗目标信号丢失方法。
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