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A Knowledge Engineering Method for Track Initiation in Complex Conditions

机译:复杂条件下航迹启动的知识工程方法

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In a complex environment radar plot is often changing dramatically, non-uniform, discontinuous, uncertain and containing lots of false alarms. It is difficult for tracking system to form tracks in such complex environment. Traditional track formation methods can not accurately determine the size of track initiation gate and select specific initiation criteria. In this paper, an intelligent information processing method is proposed to solve track initiation in complex environments. The track initiation is considered as a progress of plot identification, classification and fuzzy information processing. According to the integration and fusion of neural network (NN), fuzzy reasoning (FR) and expert system (ES) technology, an intellectualized track initiation knowledge reasoning system is constructed which can realize structural, functional, algorithmic and hierarchical complementation. Further more the adaptive robust learning algorithm and the weighted synthesis reasoning algorithm are used in this system. Real data experiment shows that the proposed knowledge engineering method can effectively solve track initiation problem in complex conditions.
机译:在复杂的环境中,雷达绘图通常在显着变化,不均匀,不连续,不确定和包含大量的误报。跟踪系统难以在这种复杂环境中形成曲目。传统的轨道形成方法无法准确地确定轨道启动门的大小,并选择特定的启动标准。本文提出了一种智能信息处理方法来解决复杂环境中的轨道启动。轨道启动被认为是绘图识别,分类和模糊信息处理的进度。根据神经网络(NN)的集成和融合,模糊推理(FR)和专家系统技术,构建了一种智能化的轨道启动知识推理系统,其可以实现结构,功能,算法和分层互补。此外,在该系统中使用自适应稳健的学习算法和加权综合推理算法。实际数据实验表明,所提出的知识工程方法可以有效地解决复杂条件下的轨道启动问题。

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