Efficient FPGA-based Object Detection Solution for Autonomous Driving
(Portland Institute, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)
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
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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.