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Small Target Detection for FOD Millimeter-Wave Radar Based on Compressed Imaging

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Foreign object debris (FOD) radar systems are often used to detect foreign materials that appear on the pavement that can pose as a threat to aircraft and personnel. Scan-mode millimeter-wave… Click to show full abstract

Foreign object debris (FOD) radar systems are often used to detect foreign materials that appear on the pavement that can pose as a threat to aircraft and personnel. Scan-mode millimeter-wave (MMW) radar with a fixed installation position is widely used as a leading solution. Small target detection is a puzzling challenge that requires a breakthrough for practical application. The conventional matched filter (MF) process along the range would encounter frequency leakage when strong scattering targets generate high sidelobe and mutual shield interference to object detection. The compressed sensing (CS) approach used for detection achieves efficiency by suppressing sidelobes and preventing small targets from being submerged by larger targets. The compressed imaging is introduced to retrieve the image scene with higher resolution and a small detectable object, such as 2-cm-diameter metal ball that equals −35-dBsm radar cross section (RCS). The long stripes scattering phenomenon can be reduced, which is beneficial to further detection processing. Furthermore, we demonstrate the concept of the MMW radar detection approach based on compressed imaging with the actual data. It validates the improved efficiency in at least two conditions: a small interval between multiple targets and strong scattering coverage of small targets. Nevertheless, we highlight some previously unrealized benefits of the FOD radar system application. There is no prior detection approach based on compressed imaging to enhance the performance of an FOD radar, as we present in this study.

Keywords: compressed imaging; fod; based compressed; millimeter wave; detection; radar

Journal Title: IEEE Geoscience and Remote Sensing Letters
Year Published: 2022

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