FDA-MIMO-DFRC 系统的 LPI 波形和无源波束成形联合设计

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Long Du , Shunsheng Zhang , Libing Huang , Wen-Qin Wang
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引用次数: 0

摘要

双功能雷达-通信(DFRC)系统已被公认为无线通信领域最有前途的技术之一。然而,DFRC 系统的低截获概率(LPI)性能不容忽视。基于频率多样化阵列多输入多输出(FDA-MIMO)雷达,我们提出了一种 DFRC 系统,以增强杂波环境中的目标探测能力,并针对潜在的敌方拦截器实现理想的 LPI。这个问题可以转化为一个优化问题,即在要求的 LPI 性能和恒定模数波形约束三个指标之一下,最大化雷达信号干扰加噪声比(SINR),同时满足每个用户的通信服务质量(QoS)要求。为了解决这个具有挑战性的问题,我们借助一个辅助变量,将其重新表述为一个等价但更容易理解的形式。随后,我们采用替代方向乘法(ADMM)和主要化-最小化(MM)算法来解决由此产生的问题。仿真结果验证了所提出的 LPI FDA-MIMO-DFRC 方案的传感性能优于传统的 MIMO 方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint LPI waveform and passive beamforming design for FDA-MIMO-DFRC systems
Dual-functional Radar-Communication (DFRC) systems have been recognized as one of the most promising technologies in the field of wireless communications. Nevertheless, the low probability of intercept (LPI) performance in the DFRC systems cannot be overlooked. Based on the frequency diverse array multiple-input–multiple output (FDA-MIMO) radar, a DFRC system is proposed to enhance target detection in clutter environment and achieve desirable LPI against an underlying hostile interceptor. The issue can be cast into an optimization problem that maximizes the radar signal-to-interference-plus-noise ratio (SINR) while satisfying the communication quality-of-service (QoS) requirement of each user under one of three metrics, the required LPI performance and the constant-modulus waveform constraint. To solve this challenging problem, we reformulate it into an equivalent but more tractable form by resorting to an auxiliary variable. Subsequently, we employ the alternative direction method of multipliers (ADMM) and majorization-minimization (MM) algorithms to solve the resultant problem. Simulation results validate that the proposed LPI FDA-MIMO-DFRC scheme exhibits superior sensing performance over the conventional scheme with MIMO.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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