基于ESM数据的目标识别
Object Recognition and Identification Using ESM Data
摘要：
对未知目标的识别是监控和安全系统中的一项重要任务。电子支援措施（ESM）是最有效的识别传感器之一，特别是在海上和空对地应用中。在典型的监视系统中，多个ESM传感器通常与雷达等运动传感器一起部署。不同的ESM传感器可以产生准备发送到融合中心的不同类型的报告。本文的重点是发展一种新的体系结构的目标识别和识别时，非均匀ESM和可能的运动报告收到的融合中心。新的融合架构进行评估，使用模拟显示利用不同的ESM报告，如属性和信号级ESM数据的好处。
英文摘要：
Recognition and identification of unknown targets is a crucial task in surveillance and security systems. Electronic Support Measures (ESM) are one of the most effective sensors for identification, especially for maritime and air--to--ground applications. In typical surveillance systems multiple ESM sensors are usually deployed along with kinematic sensors like radar. Different ESM sensors may produce different types of reports ready to be sent to the fusion center. The focus of this paper is to develop a new architecture for target recognition and identification when non--homogeneous ESM and possibly kinematic reports are received at the fusion center. The new fusion architecture is evaluated using simulations to show the benefit of utilizing different ESM reports such as attributes and signal level ESM data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
