本文描述科霍内(Kohonen)特征映射神经网络模型对于战术和传感器数据融合的应用。用来自现代海军环境的例子评述由数据融合提出的问题。强调了用于海军作战自动监视和支持的目标和任务识别。作为基于神经网络的系统的可应用领域评述了科霍内特征映射模型,研究了它在实际应用中的限制,讨论了如何解决这些问题。描述了使用科霍内特征映射作为基本单元的两个不同的模块化神经网络体系结构和它们应用于数据融合的比较。 This article describes the application of the Kohonen feature mapping neural network model to tactical and sensor data fusion. An example from the modern naval environment reviews issues raised by data fusion. Emphasizes goals and task identification for automatic surveillance and support of naval operations. The Kehnenet feature mapping model is reviewed as an applicable field of neural network-based systems. Its limitations in practical applications are discussed, and how to solve these problems is discussed. Describes two different modular neural network architectures that use Kehnenet’s signature as a basic unit and their application to data fusion.