基于正交频分复用的双功能雷达通信系统的循环码阵列信号设计

IF 1.1 4区 工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC IET Signal Processing Pub Date : 2023-06-22 DOI:10.1049/sil2.12231
Yu Zhou, Wen Ren, Qiuyue Zhang, Sisi Chen, Linrang Zhang
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引用次数: 0

摘要

为了解决雷达与通信系统在波束扫描和波束覆盖方面的矛盾,提出了一种基于循环码阵的双功能雷达通信系统。通过循环码阵列传输处理后的正交频分复用(OFDM)信号作为基信号,提高数据传输速率。按照通信接收机的空间角度,将通信符号调制为占用特定频带的OFDM信号子载波的一部分。循环码阵列的一个重要特性是提供了基信号的基带频率与空间角度之间的关系,为向合作接收机和解调的安全电信传输提供了基础。此外,循环码阵列传输相同的信号并在相邻阵列元素之间引入相同的时间间隔。因此,将传统基于多输入多输出的DFRC系统设计中多维正交信号设计的复杂问题转化为简单的基信号设计。最后,得到了全向覆盖图。这样,无论通信接收机位于雷达波束的主瓣还是旁瓣,所设计的DFRC系统都可以与通信用户建立通信连接。通过理论分析和仿真验证了该系统的性能。
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Orthogonal frequency-division multiplexing-based signal design for a dual-function radar-communications system using circulating code array

In this study, a dual-function radar-communications (DFRC) system based on the circulating code array is presented to address the contradiction between radar and communications system in beam scanning and beam coverage. Processed orthogonal frequency-division multiplexing (OFDM) signal is transmitted by the circulating code array as the base signal to improve the data rate. Following the spatial angle of the communication receiver, the communication symbols are modulated to part of OFDM signal subcarriers occupying a specific frequency band. A significant property of the circulating code array, which provides a relationship between the baseband frequency of the base signal and the spatial angles, implements a basis for safe telecommunication transmission towards the cooperative receiver and demodulation. Moreover, the circulating code array transmits the same signal and introduces the same time interval between adjacent array elements. Therefore, the complex problems of multi-dimensional orthogonal signal design in the traditional multiple-input-multiple-output-based DFRC system design are transformed into a simple base signal design. Finally, an omnidirectional coverage pattern is obtained. Thus, whether the communication receiver is in the mainlobe or the sidelobe of the radar beam, the communication connection can be established between the designed DFRC system and the communication users. The performance of the described DFRC system is verified through theoretical analysis and simulations.

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来源期刊
IET Signal Processing
IET Signal Processing 工程技术-工程:电子与电气
CiteScore
3.80
自引率
5.90%
发文量
83
审稿时长
9.5 months
期刊介绍: IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems. The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more. Topics covered by scope include, but are not limited to: advances in single and multi-dimensional filter design and implementation linear and nonlinear, fixed and adaptive digital filters and multirate filter banks statistical signal processing techniques and analysis classical, parametric and higher order spectral analysis signal transformation and compression techniques, including time-frequency analysis system modelling and adaptive identification techniques machine learning based approaches to signal processing Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques theory and application of blind and semi-blind signal separation techniques signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals direction-finding and beamforming techniques for audio and electromagnetic signals analysis techniques for biomedical signals baseband signal processing techniques for transmission and reception of communication signals signal processing techniques for data hiding and audio watermarking sparse signal processing and compressive sensing Special Issue Call for Papers: Intelligent Deep Fuzzy Model for Signal Processing - https://digital-library.theiet.org/files/IET_SPR_CFP_IDFMSP.pdf
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