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Data Fusion: A Conceptual Approach to Level 2 Fusion (Situational Assessment)

机译:数据融合:2级融合的概念方法(状况评估)

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Level 2 fusion is defined as situation assessment. Unfortunately, that is the point where the agreement on Level 2 fusion ends. The distinctions between the boundaries between Levels 1, 2, and 3 are not clearly defined. As a result, these disputes tend to cloud the discussion on the required functionality required of a Level 2 tracking system. Our approach to develop a system that solves a perceived Level 2 problem has three basic tenets: define the problem, develop the concept of the fusion architecture, and define the object state. These tenets provide the foundation to outline and explain the conceptual approach to a Level 2 problem. Each step from the problem fundamentals to the state definition used in the formulation of algorithmic approaches is presented. The discussion begins with a summary of the military problem, which can be considered situation assessment, of multiple levels of unit aggregation to determine force composition, current capabilities, and posture. The problem consists of fusion Level 1 information, incorporating doctrine and other knowledge base information to form a coherent scene of what exists in the field that can then be used as a component of intent analysis. The development of the problem model leads to the development of a Fusion architecture approach. The approach mirrors one of the standard approaches of Level 1 fusion: detection, prediction, association, hypothesis generation and management, and update. Unlike the Level 1 problem, these implementation steps will not become a rehash of the Kalman filter or similar approaches. Instead, the architecture permits a composite set of approaches, including symbolic methodologies. The problem definition and the architecture lead to the development of the system state that represents the internal composition of the units and their aggregates. From this point, the discussion concludes with a short summary of potential algorithms proposed for implementation.
机译:2级融合定义为情况评估。不幸的是,这就是关于第2级融合的协议的终结点。 1、2和3级之间的边界之间的区别没有明确定义。结果,这些争执往往使关于2级跟踪系统所需功能的讨论蒙上阴影。我们开发用于解决2级感知问题的系统的方法具有三个基本原则:定义问题,开发融合体系结构的概念以及定义对象状态。这些原则为概述和解释解决2级问题的概念方法提供了基础。提出了从问题基础到算法定义方法中使用的状态定义的每个步骤。讨论从对军事问题的总结开始,可以将其视为情况评估,以多个级别的单位聚集来确定部队组成,当前能力和状态。该问题由1级信息融合而成,并结合了学说和其他知识库信息,形成了该领域存在的连贯场景,然后可以用作意图分析的组成部分。问题模型的发展导致融合架构方法的发展。该方法反映了1级融合的标准方法之一:检测,预测,关联,假设生成和管理以及更新。与第1级问题不同,这些实现步骤不会成为卡尔曼滤波器或类似方法的重提。相反,该体系结构允许使用一组复合方法,包括符号方法。问题定义和体系结构导致系统状态的发展,该系统状态表示单元及其集合的内部组成。从这一点出发,讨论以提议实现的潜在算法的简短总结结束。

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