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基于低截获概率的雷达波形设计,用于杂波环境下分布式多雷达与无线通信系统的频谱共存

Low Probability of Intercept-Based Radar Waveform Design for Spectral Coexistence of Distributed Multiple-Radar and Wireless Communication Systems in Clutter.

作者信息

Shi Chenguang, Wang Fei, Salous Sana, Zhou Jianjiang

机构信息

Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

School of Engineering and Computing Sciences, Durham University, Durham DH1 3DE, UK.

出版信息

Entropy (Basel). 2018 Mar 16;20(3):197. doi: 10.3390/e20030197.

Abstract

In this paper, the problem of low probability of intercept (LPI)-based radar waveform design for distributed multiple-radar system (DMRS) is studied, which consists of multiple radars coexisting with a wireless communication system in the same frequency band. The primary objective of the multiple-radar system is to minimize the total transmitted energy by optimizing the transmission waveform of each radar with the communication signals acting as interference to the radar system, while meeting a desired target detection/characterization performance. Firstly, signal-to-clutter-plus-noise ratio (SCNR) and mutual information (MI) are used as the practical metrics to evaluate target detection and characterization performance, respectively. Then, the SCNR- and MI-based optimal radar waveform optimization methods are formulated. The resulting waveform optimization problems are solved through the well-known bisection search technique. Simulation results demonstrate utilizing various examples and scenarios that the proposed radar waveform design schemes can evidently improve the LPI performance of DMRS without interfering with friendly communications.

摘要

本文研究了基于低截获概率(LPI)的分布式多雷达系统(DMRS)雷达波形设计问题,该系统由多个与无线通信系统在同一频段共存的雷达组成。多雷达系统的主要目标是通过优化每个雷达的发射波形,在将通信信号视为雷达系统干扰的情况下,使总发射能量最小化,同时满足期望的目标检测/特征描述性能。首先,分别使用信杂噪比(SCNR)和互信息(MI)作为评估目标检测和特征描述性能的实际指标。然后,制定了基于SCNR和MI的最优雷达波形优化方法。通过著名的二分搜索技术解决由此产生的波形优化问题。仿真结果利用各种示例和场景表明,所提出的雷达波形设计方案能够在不干扰友好通信的情况下,显著提高DMRS的LPI性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd7e/7512714/93502294aef1/entropy-20-00197-g001.jpg

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