Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR) has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies...

Full description

Bibliographic Details
Main Authors: Bo Zhang, Chao Wang, Hong Zhang, Fan Wu, Yi-Xian Tang
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/17/2/298
_version_ 1811305563846344704
author Bo Zhang
Chao Wang
Hong Zhang
Fan Wu
Yi-Xian Tang
author_facet Bo Zhang
Chao Wang
Hong Zhang
Fan Wu
Yi-Xian Tang
author_sort Bo Zhang
collection DOAJ
description By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR) has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP) SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.
first_indexed 2024-04-13T08:27:43Z
format Article
id doaj.art-346c4aa73e6847b5b1489f9c07e96d70
institution Directory Open Access Journal
issn 1424-8220
language English
last_indexed 2024-04-13T08:27:43Z
publishDate 2017-02-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj.art-346c4aa73e6847b5b1489f9c07e96d702022-12-22T02:54:21ZengMDPI AGSensors1424-82202017-02-0117229810.3390/s17020298s17020298Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic MonitoringBo Zhang0Chao Wang1Hong Zhang2Fan Wu3Yi-Xian Tang4Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaBy acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR) has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP) SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.http://www.mdpi.com/1424-8220/17/2/298Synthetic Aperture Radarvehicle detectabilityRadarsat-2 satellitetraffic monitoring
spellingShingle Bo Zhang
Chao Wang
Hong Zhang
Fan Wu
Yi-Xian Tang
Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
Sensors
Synthetic Aperture Radar
vehicle detectability
Radarsat-2 satellite
traffic monitoring
title Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
title_full Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
title_fullStr Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
title_full_unstemmed Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
title_short Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring
title_sort detectability analysis of road vehicles in radarsat 2 fully polarimetric sar images for traffic monitoring
topic Synthetic Aperture Radar
vehicle detectability
Radarsat-2 satellite
traffic monitoring
url http://www.mdpi.com/1424-8220/17/2/298
work_keys_str_mv AT bozhang detectabilityanalysisofroadvehiclesinradarsat2fullypolarimetricsarimagesfortrafficmonitoring
AT chaowang detectabilityanalysisofroadvehiclesinradarsat2fullypolarimetricsarimagesfortrafficmonitoring
AT hongzhang detectabilityanalysisofroadvehiclesinradarsat2fullypolarimetricsarimagesfortrafficmonitoring
AT fanwu detectabilityanalysisofroadvehiclesinradarsat2fullypolarimetricsarimagesfortrafficmonitoring
AT yixiantang detectabilityanalysisofroadvehiclesinradarsat2fullypolarimetricsarimagesfortrafficmonitoring