Joint range and velocity super-resolution estimation with Doppler effects for innovative OFDM-based RFA RadCom system

IF 2.9 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Digital Signal Processing Pub Date : 2024-10-15 DOI:10.1016/j.dsp.2024.104805
Wenxu Zhang , Hao Wan , Zhongkai Zhao , Manjun Lu
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Abstract

Conventional radar and communication signals face challenges when integrating for accurate sensing in dense electromagnetic environments, especially in scenarios involving high-velocity targets estimation. To address this issue, we propose the random frequency agile-orthogonal frequency division multiplexing-based radar and communication (RFA-OFDM-based RadCom) signal, a novel framework that combines RFA hopping radar signal and OFDM signal. This framework effectively handles high-velocity Doppler scenarios, enhancing electronic countermeasure capabilities. In high-velocity scenarios, achieving accurate range and velocity estimation is crucial. We introduce a comprehensive received signal model that considers intrapulse and intersubcarrier Doppler effects, often overlooked in traditional high-velocity contexts. The proposed two-phase hierarchical perceptual methodology enables joint super-resolution estimation using the shared signal. We transform the shared signal echo model into a uniform linear array-like model and employ the matrix decomposition algorithm based on bidirectional weighted frequency smoothing (BWFS-MD) for decoherence processing. Subsequently, the estimation of signal parameters via rotational invariance techniques (ESPRIT)-complementary integrated subspace fitting (E-CISF) algorithm accurately estimates joint range and velocity. Meanwhile, the contrastive analysis of the mutual impacts between radar and communication functions is conducted. Theoretical analysis and simulation results robustly validate the superior performance of the proposed BWFS-MD algorithm. Furthermore, considering the precision of joint range-velocity estimation, real-time constraints, and super-resolution capability (which is emphasized), the E-CSIF algorithm demonstrates the best overall performance from a comprehensive perspective.
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利用多普勒效应对基于 OFDM 的创新型 RFA RadCom 系统进行联合测距和速度超分辨率估算
传统的雷达和通信信号在密集电磁环境中进行整合以实现精确感知时面临挑战,尤其是在涉及高速目标估计的场景中。为解决这一问题,我们提出了基于随机频率敏捷-正交频分复用技术的雷达和通信(RFA-OFDM-based RadCom)信号,这是一种将随机频率敏捷跳变雷达信号和正交频分复用技术信号相结合的新型框架。该框架可有效处理高速多普勒场景,增强电子对抗能力。在高速场景中,实现精确的测距和速度估计至关重要。我们引入了一个全面的接收信号模型,该模型考虑了脉冲内和子载波间的多普勒效应,而这些效应在传统的高速情况下往往被忽视。所提出的两阶段分层感知方法能够利用共享信号进行联合超分辨率估计。我们将共享信号回波模型转换为均匀线性阵列模型,并采用基于双向加权频率平滑(BWFS-MD)的矩阵分解算法进行去相干处理。随后,通过旋转不变性技术(ESPRIT)-互补集成子空间拟合(E-CISF)算法估算信号参数,准确估算出关节范围和速度。同时,对雷达和通信功能之间的相互影响进行了对比分析。理论分析和仿真结果有力地验证了所提出的 BWFS-MD 算法的优越性能。此外,考虑到联合测距-测速估计的精度、实时约束和超分辨率能力(重点强调),E-CSIF 算法从综合角度展示了最佳的整体性能。
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来源期刊
Digital Signal Processing
Digital Signal Processing 工程技术-工程:电子与电气
CiteScore
5.30
自引率
17.20%
发文量
435
审稿时长
66 days
期刊介绍: Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,
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