Global Tuning for System Performance Optimization of RF MIMO Radars

Ferhat Can Ataman, Muslum Emir Avci, Chethan Kumar Y. B., S. Ozev
{"title":"Global Tuning for System Performance Optimization of RF MIMO Radars","authors":"Ferhat Can Ataman, Muslum Emir Avci, Chethan Kumar Y. B., S. Ozev","doi":"10.1109/ETS56758.2023.10174159","DOIUrl":null,"url":null,"abstract":"RF systems, including RF MIMO RADARs, are increasingly integrated with digital systems in fine-geometry processes. Due to the prevalent use of RF MIMO RADARs in automotive and other safety-critical applications, in-field testing and tuning of these systems are needed to meet performance and safety targets. The fundamental performance targets of an RF MIMO system include the signal-to-noise ratio at the end of the receiver chain, matching characteristics between different signal paths, gain, noise figure, and linearity of the RF front end. In a RADAR device, matching between signal paths affects the angular resolution of the system. The gain and noise figure of the receiver control the maximum distance and the smallest object that the system can detect. In this work, we present a global tuning algorithm for RF MIMO RADARs to meet critical system performance targets while minimizing power consumption. The efficacy of the method is demonstrated with extensive simulations and hardware experiments.","PeriodicalId":211522,"journal":{"name":"2023 IEEE European Test Symposium (ETS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE European Test Symposium (ETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETS56758.2023.10174159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

RF systems, including RF MIMO RADARs, are increasingly integrated with digital systems in fine-geometry processes. Due to the prevalent use of RF MIMO RADARs in automotive and other safety-critical applications, in-field testing and tuning of these systems are needed to meet performance and safety targets. The fundamental performance targets of an RF MIMO system include the signal-to-noise ratio at the end of the receiver chain, matching characteristics between different signal paths, gain, noise figure, and linearity of the RF front end. In a RADAR device, matching between signal paths affects the angular resolution of the system. The gain and noise figure of the receiver control the maximum distance and the smallest object that the system can detect. In this work, we present a global tuning algorithm for RF MIMO RADARs to meet critical system performance targets while minimizing power consumption. The efficacy of the method is demonstrated with extensive simulations and hardware experiments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
射频MIMO雷达系统性能优化的全局调谐
射频系统,包括射频MIMO雷达,越来越多地与精细几何过程中的数字系统集成。由于射频MIMO雷达在汽车和其他安全关键应用中的广泛使用,需要对这些系统进行现场测试和调整,以满足性能和安全目标。射频MIMO系统的基本性能指标包括接收机链末端的信噪比、不同信号路径之间的匹配特性、增益、噪声系数和射频前端的线性度。在雷达设备中,信号路径之间的匹配会影响系统的角分辨率。接收机的增益和噪声系数控制着系统能检测到的最大距离和最小目标。在这项工作中,我们提出了一种射频MIMO雷达的全局调谐算法,以满足关键的系统性能目标,同时最小化功耗。通过大量的仿真和硬件实验证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Counterfeit Detection by Semiconductor Process Technology Inspection Semi-Supervised Deep Learning for Microcontroller Performance Screening FINaL: Driving High-Level Fault Injection Campaigns with Natural Language Learn to Tune: Robust Performance Tuning in Post-Silicon Validation A Resilience Framework for Synapse Weight Errors and Firing Threshold Perturbations in RRAM Spiking Neural Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1