Performance Comparison of Beat Frequency Extraction Algorithm and Cross Correlation Algorithm for FMCW Radar Signal Processing Implemented on LabVIEW and USRP

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ) Pub Date : 2019-11-01 DOI:10.1109/HNICEM48295.2019.9073501

Jesrey Martin S. Macasero, Olga Joy L. Gerasta

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引用次数: 2

Abstract

There are two prominent ways of implementing signal processing of FMCW radar in SDRs, namely i) the Beat Frequency Extraction Algorithm and ii) Cross Correlation Algorithm. The former is done by numerical mixing of the reference signal and the received signal first and then performing an FFT to detect the beat frequency that is then processed to output range information. Moreover, the latter is done by using cross correlation on the reference signal and the received signal. The aim of this paper is to scrutinize these two algorithms when they are implemented on the NI-USRP SDR platform and determine which is best for FMCW radar target detection accuracy. This paper gives guidance on the pros and cons of choosing such algorithm when being implemented on the USRP platform with LabVIEW as the development environment. The implementation of the two systems are based on these conditions: i) Carrier signal is 2Ghz, ii) Loopback cable is RG58 with lengths= 6m, 8m, 14m, 22m, and iii) Output RF Power of device is 70mW. Given the performance criteria of this paper, the Beat Frequency algorithm performed best compared to the Cross-Correlation algorithm.

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在LabVIEW和USRP上实现的FMCW雷达信号处理中拍频提取算法和互相关算法的性能比较

在sdr中实现FMCW雷达信号处理的主要方法有两种，即拍频提取算法和互相关算法。前者是通过首先对参考信号和接收信号进行数值混合，然后执行FFT来检测拍频，然后处理以输出范围信息。后者是通过对参考信号和接收信号进行互相关来实现的。本文的目的是仔细研究这两种算法在NI-USRP SDR平台上的实现，并确定哪一种算法对FMCW雷达目标检测精度最好。本文给出了以LabVIEW为开发环境在USRP平台上实现该算法时选择该算法的利弊。两个系统的实现基于以下条件:i)载波信号为2Ghz, ii)环回电缆为RG58，长度分别为6m、8m、14m、22m, iii)设备输出RF功率为70mW。考虑到本文的性能标准，与交叉相关算法相比，拍频算法表现最好。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )

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