目标跟踪的全自适应雷达第一部分:单目标跟踪

K. Bell, C. Baker, G. Smith, J. Johnson, M. Rangaswamy
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引用次数: 40

摘要

大多数雷达系统采用前馈处理链,其中它们首先对接收到的传感器数据进行一些低级处理以获得目标检测,然后将处理后的数据传递给一些高级处理器,如跟踪器,后者提取信息以实现系统目标。利用从传感器/处理器提取的信息与后续照明波形的设计和传输之间的自适应,可以提高系统性能。因此,认知或完全自适应雷达系统提供了很大的希望。在本文中,我们开发了一个通用的全自适应雷达框架,用于雷达系统的目标跟踪。该模型包括高级跟踪处理器,并规定了获取下一组传感器数据的反馈机制和优化准则。在分配系统资源(每个传感器上的观察时间)以优化单个目标跟踪性能的分布式传感器系统上演示了性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fully adaptive radar for target tracking part I: Single target tracking
Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker, which extracts information to achieve a system objective. System performance can be improved using adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. As such, cognitive or fully adaptive radar systems offer much promise. In this paper, we develop a general fully adaptive radar framework for a radar system engaged in target tracking. The model includes the higher-level tracking processor and specifies the feedback mechanism and optimization criterion used to obtain the next set of sensor data. Performance is demonstrated on a distributed sensor system in which system resources (observation time on each sensor) are allocated to optimize single target tracking performance.
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