实现增强型并行 CFAR 架构的 SoPC FPGA

Sadok Msadaa, Younes Lahbib, A. Mami
{"title":"实现增强型并行 CFAR 架构的 SoPC FPGA","authors":"Sadok Msadaa, Younes Lahbib, A. Mami","doi":"10.1109/SETIT54465.2022.9875739","DOIUrl":null,"url":null,"abstract":"This paper presents a practical experience in designing a programmable system-on-chip for a complex and modern purpose associated with high-resolution, real-time target detection for radar systems. In this paper, an embedded architecture that merges into a single platform, the two hardware and software components. This architecture is implemented using a PC board based on a field programmable gate array (FPGA). The technique used for the detection process is the automatic censored ordered statistics detection (ACOSD) CFAR with the shared resource technique. All of which we exploit the robustness of the hardware that operates two ACOSD detector in parallel, alongside the flexibility of the software based on a microprocessor ARM Cortex A9. The hardware/software embedded system detector is developed using Xilinx Vivado high-level synthesis and Xilinx SDK. The new Hardware/Software design has been uploaded onto the Zedboard Zynq 7000 FPGA board. The design operates at a maximum frequency of 148 MHz and performs real-time target detection with an execution time of 0.24 μs, which is lower than 0.5 μs of the critical time required for high-resolution target detection.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A SoPC FPGA Implementing of an Enhanced Parallel CFAR Architecture\",\"authors\":\"Sadok Msadaa, Younes Lahbib, A. Mami\",\"doi\":\"10.1109/SETIT54465.2022.9875739\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a practical experience in designing a programmable system-on-chip for a complex and modern purpose associated with high-resolution, real-time target detection for radar systems. In this paper, an embedded architecture that merges into a single platform, the two hardware and software components. This architecture is implemented using a PC board based on a field programmable gate array (FPGA). The technique used for the detection process is the automatic censored ordered statistics detection (ACOSD) CFAR with the shared resource technique. All of which we exploit the robustness of the hardware that operates two ACOSD detector in parallel, alongside the flexibility of the software based on a microprocessor ARM Cortex A9. The hardware/software embedded system detector is developed using Xilinx Vivado high-level synthesis and Xilinx SDK. The new Hardware/Software design has been uploaded onto the Zedboard Zynq 7000 FPGA board. The design operates at a maximum frequency of 148 MHz and performs real-time target detection with an execution time of 0.24 μs, which is lower than 0.5 μs of the critical time required for high-resolution target detection.\",\"PeriodicalId\":126155,\"journal\":{\"name\":\"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SETIT54465.2022.9875739\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SETIT54465.2022.9875739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文介绍了设计可编程片上系统的实际经验,该系统用于雷达系统的高分辨率、实时目标检测等复杂的现代用途。在本文中,一种嵌入式架构将硬件和软件两个组件合并到一个平台中。该架构是通过一块基于现场可编程门阵列(FPGA)的 PC 板实现的。检测过程中使用的技术是带有共享资源技术的自动删减有序统计检测(ACOSD)CFAR。我们利用硬件的鲁棒性并行操作两个 ACOSD 检测器,同时利用基于 ARM Cortex A9 微处理器的软件的灵活性。硬件/软件嵌入式系统检测器是使用 Xilinx Vivado 高级合成和 Xilinx SDK 开发的。新的硬件/软件设计已上传至 Zedboard Zynq 7000 FPGA 板。该设计的最高工作频率为 148 MHz,可执行实时目标检测,执行时间为 0.24 μs,低于高分辨率目标检测所需的临界时间 0.5 μs。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A SoPC FPGA Implementing of an Enhanced Parallel CFAR Architecture
This paper presents a practical experience in designing a programmable system-on-chip for a complex and modern purpose associated with high-resolution, real-time target detection for radar systems. In this paper, an embedded architecture that merges into a single platform, the two hardware and software components. This architecture is implemented using a PC board based on a field programmable gate array (FPGA). The technique used for the detection process is the automatic censored ordered statistics detection (ACOSD) CFAR with the shared resource technique. All of which we exploit the robustness of the hardware that operates two ACOSD detector in parallel, alongside the flexibility of the software based on a microprocessor ARM Cortex A9. The hardware/software embedded system detector is developed using Xilinx Vivado high-level synthesis and Xilinx SDK. The new Hardware/Software design has been uploaded onto the Zedboard Zynq 7000 FPGA board. The design operates at a maximum frequency of 148 MHz and performs real-time target detection with an execution time of 0.24 μs, which is lower than 0.5 μs of the critical time required for high-resolution target detection.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Comparison of Machine Learning Methods for best Accuracy COVID-19 Diagnosis Using Chest X-Ray Images Design and Simulation of a PV System Controlled through a Hybrid INC-PSO Algorithm using XSG Tool Analysing ICT Initiatives towards Smart Policing to Assist African Law Enforcement in Combating Cybercrimes Preliminary Study Of A Smart Computer System For Scholar Support Distributed Consensus Control for Multi-Agent Oscillatory Systems
×
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