Daniel Vriesman, Bernhard Thoresz, Dagmar Steinhauser, A. Zimmer, A. Britto, T. Brandmeier
{"title":"An Experimental Analysis of Rain Interference on Detection and Ranging Sensors","authors":"Daniel Vriesman, Bernhard Thoresz, Dagmar Steinhauser, A. Zimmer, A. Britto, T. Brandmeier","doi":"10.1109/ITSC45102.2020.9294505","DOIUrl":null,"url":null,"abstract":"Performing high level autonomous navigation in a reliable and robust way considering different ambient conditions is a very challenging task. To achieve this goal, a mix of different sensors, such as cameras, lidars, and radars, are normally used to gather information from the environment. Since each sensor works based on different physical principles, they are affected differently by the challenging conditions, like weather interference for example. Looking to explore the influence of high intensity rain (98mm/h), this paper presents a robust experimental protocol that analyzes the influence inside the near field of lidar and radar sensors. The results shows how the effect of rain droplets degrades the backscattering signal from both sensors, affecting the information regarding the target’s dimension. The consequences in terms object and feature detection’es changes are also discussed.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC45102.2020.9294505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Performing high level autonomous navigation in a reliable and robust way considering different ambient conditions is a very challenging task. To achieve this goal, a mix of different sensors, such as cameras, lidars, and radars, are normally used to gather information from the environment. Since each sensor works based on different physical principles, they are affected differently by the challenging conditions, like weather interference for example. Looking to explore the influence of high intensity rain (98mm/h), this paper presents a robust experimental protocol that analyzes the influence inside the near field of lidar and radar sensors. The results shows how the effect of rain droplets degrades the backscattering signal from both sensors, affecting the information regarding the target’s dimension. The consequences in terms object and feature detection’es changes are also discussed.