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Cognitive Frequency-Hopping Waveform Design for Dual-Function MIMO Radar-Communications System

机译:双功能MIMO雷达通信系统的认知跳频波形设计

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摘要

A frequency-hopping (FH)-based dual-function multiple-input multiple-output (MIMO) radar communications system enables implementation of a primary radar operation and a secondary communication function simultaneously. The set of transmit waveforms employed to perform the MIMO radar task is generated using FH codes. For each transmit antenna, the communication operation can be realized by embedding one phase symbol during each FH interval. However, as the radar channel is time-variant, it is necessary for a successive waveform optimization scheme to continually obtain target feature information. This research work aims at enhancing the target detection and feature estimation performance by maximizing the mutual information (MI) between the target response and the target returns, and then minimizing the MI between successive target-scattering signals. The two-step cognitive waveform design strategy is based upon continuous learning from the radar scene. The dynamic information about the target feature is utilized to design FH codes. Simulation results show an improvement in target response extraction, target detection probability and delay-Doppler resolution as the number of iterations increases, while still maintaining high data rate with low bit error rates between the proposed system nodes.
机译:基于跳频(FH)的双功能多输入多输出(MIMO)雷达通信系统可同时实现主要雷达操作和辅助通信功能。使用FH代码生成用于执行MIMO雷达任务的一组发射波形。对于每个发射天线,可以通过在每个FH间隔内嵌入一个相位符号来实现通信操作。但是,由于雷达信道是随时间变化的,因此连续波形优化方案有必要连续获取目标特征信息。这项研究工作旨在通过最大化目标响应和目标返回之间的互信息(MI),然后最小化连续的目标散射信号之间的MI来增强目标检测和特征估计性能。两步认知波形设计策略基于对雷达场景的持续学习。有关目标特征的动态信息用于设计FH代码。仿真结果表明,随着迭代次数的增加,目标响应提取,目标检测概率和延迟多普勒分辨率得到了改善,同时在所建议的系统节点之间仍保持了高数据速率和低误码率。

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