基于最大SINR和MI的认知雷达波形设计

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI:10.1109/ITNEC48623.2020.9084764

Qingpei Yang, C. Shang, Jian Dong

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引用次数: 2

摘要

在真实战场中，雷达目标的先验信息是不容易获得的。基于雷达目标先验信息的波形不能满足检测和参数估计的需要。本文研究了不同任务能量约束下的最优波形设计方法。为了提高雷达系统的探测性能，可以最大化已知和随机扩展目标的信噪比(SINR);为了提高参数估计的性能，使雷达回波与随机目标频谱响应之间的互信息(MI)最大化，进行了最优波形设计和仿真。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Waveform Design of Cognitive Radar Based on Maximum SINR and MI

In real battlefield, the prior information of radar target is not easy to obtain. The waveform based on the prior information of radar target can not meet the needs of detection and parameter estimation. This paper considers the optimal waveform design method under different task energy constraints. In order to improve the detection performance of radar system, the signal-to-interference-to-noise ratio (SINR) of known and random extended targets can be maximized; in order to improve the performance of parameter estimation, the mutual information (MI) between radar echo and spectrum response of random targets can be maximized, and the optimal waveform design and simulation are carried out.

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来源期刊

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

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