FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar

Using millimeter-wave radar to scan and detect small foreign object debris (FOD) on an airport runway surface is a popular solution in civil aviation safety. Since it is impossible to completely eliminate the interference reflections arising from strongly scattering targets or non-homogeneous clutte...

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Main Authors: Yangliang Wan, Xingdong Liang, Xiangxi Bu, Yunlong Liu
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/4/1241
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author Yangliang Wan
Xingdong Liang
Xiangxi Bu
Yunlong Liu
author_facet Yangliang Wan
Xingdong Liang
Xiangxi Bu
Yunlong Liu
author_sort Yangliang Wan
collection DOAJ
description Using millimeter-wave radar to scan and detect small foreign object debris (FOD) on an airport runway surface is a popular solution in civil aviation safety. Since it is impossible to completely eliminate the interference reflections arising from strongly scattering targets or non-homogeneous clutter after clutter cancellation processing, the consequent high false alarm probability has become a key problem to be solved. In this article, we propose a new FOD detection method for interference suppression and false alarm reduction based on an iterative adaptive approach (IAA) algorithm, which is a non-parametric, weighted least squares-based iterative adaptive processing approach that can provide super-resolution capability. Specifically, we first obtain coarse FOD target information by data preprocessing in a conventional detection method. Then, a refined data processing step is conducted based on the IAA algorithm in the azimuth direction. Finally, multiple pieces of information from the two steps above are used to comprehensively distinguish false alarms by fusion processing; thus, we can acquire accurate FOD target information. Real airport data measured by a 93 GHz radar are used to validate the proposed method. Experimental results of the test scene, which include golf balls with a diameter of 43 mm, were placed about 300 m away from radar, which show that the proposed method can effectively reduce the number of false alarms when compared with a traditional FOD detection method. Although metal balls with a diameter of 50 mm were placed about 660 m away from radar, they also can obtain up to 2.2 times azimuth super-resolution capability.
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spelling doaj.art-dc4a2a901f7542a5bca848d3fbd8b35b2023-12-03T13:09:19ZengMDPI AGSensors1424-82202021-02-01214124110.3390/s21041241FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave RadarYangliang Wan0Xingdong Liang1Xiangxi Bu2Yunlong Liu3National Key Lab of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaNational Key Lab of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaNational Key Lab of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaNational Key Lab of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaUsing millimeter-wave radar to scan and detect small foreign object debris (FOD) on an airport runway surface is a popular solution in civil aviation safety. Since it is impossible to completely eliminate the interference reflections arising from strongly scattering targets or non-homogeneous clutter after clutter cancellation processing, the consequent high false alarm probability has become a key problem to be solved. In this article, we propose a new FOD detection method for interference suppression and false alarm reduction based on an iterative adaptive approach (IAA) algorithm, which is a non-parametric, weighted least squares-based iterative adaptive processing approach that can provide super-resolution capability. Specifically, we first obtain coarse FOD target information by data preprocessing in a conventional detection method. Then, a refined data processing step is conducted based on the IAA algorithm in the azimuth direction. Finally, multiple pieces of information from the two steps above are used to comprehensively distinguish false alarms by fusion processing; thus, we can acquire accurate FOD target information. Real airport data measured by a 93 GHz radar are used to validate the proposed method. Experimental results of the test scene, which include golf balls with a diameter of 43 mm, were placed about 300 m away from radar, which show that the proposed method can effectively reduce the number of false alarms when compared with a traditional FOD detection method. Although metal balls with a diameter of 50 mm were placed about 660 m away from radar, they also can obtain up to 2.2 times azimuth super-resolution capability.https://www.mdpi.com/1424-8220/21/4/1241foreign object debris (FOD)millimeter-wave radariterative adaptive approach (IAA)interference suppressionfalse alarms reductionsuper-resolution
spellingShingle Yangliang Wan
Xingdong Liang
Xiangxi Bu
Yunlong Liu
FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
Sensors
foreign object debris (FOD)
millimeter-wave radar
iterative adaptive approach (IAA)
interference suppression
false alarms reduction
super-resolution
title FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
title_full FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
title_fullStr FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
title_full_unstemmed FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
title_short FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar
title_sort fod detection method based on iterative adaptive approach for millimeter wave radar
topic foreign object debris (FOD)
millimeter-wave radar
iterative adaptive approach (IAA)
interference suppression
false alarms reduction
super-resolution
url https://www.mdpi.com/1424-8220/21/4/1241
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AT xingdongliang foddetectionmethodbasedoniterativeadaptiveapproachformillimeterwaveradar
AT xiangxibu foddetectionmethodbasedoniterativeadaptiveapproachformillimeterwaveradar
AT yunlongliu foddetectionmethodbasedoniterativeadaptiveapproachformillimeterwaveradar