Article Details

Title · Authors · Abstract · Keywords · DOI · References

Efficient FPGA-based Object Detection Solution for Autonomous Driving

LIU Yuzhou

(Portland Institute, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Section:Electronic Engineering · Vol. 2026, Issue 6 · Pages:7-11 · 2096-4706(2026)06-0007-05 · CLC number:TN952 · Document code:A · DOI:10.19850/j.cnki.2096-4706.2026.06.002

Abstract

With the rapid development of intelligent driving and unmanned systems, environmental perception imposes higher requirements on the accuracy and real-time performance of radar sensors. This paper presents an efficient millimeter-wave radar target detection system based on an FPGA-based hardware-software co-design approach. The system uses the PZ7020 as the core processing unit, combined with LD2450 and LD2451 millimeter-wave radars, and achieves high-speed multi-target information transmission via UART, and performs data acquisition, buffering, filtering, and parsing on the FPGA. On the software side, a data frame parsing program based on interrupt and buffer mechanisms is designed to ensure the completeness and real-time performance of data reception. Experimental results show that the system can stably output target distance, velocity, and angle information, with an accuracy exceeding 86% and error ranges within acceptable limits for engineering applications, demonstrating the feasibility and practicality of the proposed solution.

Keywords

FPGA acceleration; millimeter-wave radar; Object Detection; embedded data parsing

References

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About the authors

Liu Yuzhou (October 2004-), male, Han ethnicity, born in Nanjing, Jiangsu Province, is currently pursuing a bachelor's degree with a research focus on communication engineering.