A flexible, efficient and low-cost experimental platform for FMCW radars. Issue 4 (30th May 2019)

• Record Type: Journal Article
• Authors: Wang, Tao; Li, Ping; Wang, Mingfang; Yang, DanDan; Shi, Chaoyu
• Is Part Of: Sensor review. Volume 39:Issue 4(2019)
• Page Start: 495
• Page End: 503
• Publication Date: 2019-05-30
• Subjects: FMCW -- Radar -- Automation -- Experimental platform -- DTFT; Sensor systems -- Periodicals; Detectors -- Industrial applications -- Periodicals; Engineering instruments -- Periodicals; 681.2
• DOI: 10.1108/SR-07-2018-0169
• Languages: English
• ISSNs: 0260-2288

Abstract

Abstract : Purpose: This paper proposes a design of an efficient and automated experimental platform for frequency modulated continuous wave (FMCW) radars. The platform can quickly flexibly generate the waveform that meets measurement requirements and significantly improve experimental efficiency. Design/methodology/approach: This platform not only includes radio frequency devices but also integrates a programmable transmitter based on field programmable gate array. By configuring the waveform data, the experimental platform can generate waveforms with adjustable parameters and realize automatic emission, reception and processing of signals. Different from traditional fast Fourier transform, this paper uses a discrete-time Fourier transform to process low-frequency signals to get more accurate results. Findings: The authors demonstrate the effectiveness of the platform through a single-path cable experiment, an indoor ranging experiment by using different modulating waveforms and a speed measurement experiment. With complete functions and strong flexibility, the platform can operate effectively in various conditions and greatly improve the efficiency of research and study. Practical implications: The platform can accelerate the research studies and applications of FMCW radars in the fields of automatic drive, through-wall detection and health-care applications. Originality/value: Cost and functionality are taken into account in the platform, which can significantly improve the efficiency of research. The proposed signal processing method improves the accuracy while its computation complexity does not increase significantly.