This article handles the topic of cognitive radar (CR) architecture design in the framework of multifunction radar operating in a resource-constrained and spectrum-constrained environment. Despite the advances in this field of research and its relative technologies, the way humans and echolocation mammals are able to interact with the external environment goes beyond the capability of any available man-made system. A CR can be thought as a system in which the transmitter, receiver, and software parameters can be changed over time in response to the observed scene with the aim to optimize radar performances given limited resources and environment constraints. The radar, therefore, has to reason about what is being observed and has to take decisions about how to use its limited resources to improve its performance. Rules may represent the way the system reasons, while performance encodes the information contained into the received echoes, and can be used to control next actions and system memory. A rule-based cognitive architecture is proposed in this article as a way to design a CR that has to manage its resources dynamically while handling several tasks, such as target detection, imaging, and recognition in a complex and changing scenario.

中文翻译：

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用于目标检测和成像的基于规则的认知雷达设计

本文在资源受限和频谱受限环境中运行的多功能雷达框架中处理认知雷达 (CR) 架构设计主题。尽管这一研究领域及其相关技术取得了进展，但人类和回声定位哺乳动物与外部环境互动的方式超出了任何可用人造系统的能力。CR 可以被认为是一个系统，其中发射器、接收器和软件参数可以随着时间的推移响应观察到的场景而改变，目的是在有限的资源和环境约束下优化雷达性能。因此，雷达必须对观察到的内容进行推理，并且必须决定如何使用其有限的资源来提高其性能。规则可能代表系统推理的方式，而性能将包含在接收到的回声中的信息编码，并可用于控制下一步动作和系统内存。本文提出了一种基于规则的认知架构，作为设计 CR 的一种方式，该 CR 必须动态管理其资源，同时在复杂且不断变化的场景中处理多项任务，例如目标检测、成像和识别。