Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726535
Konstantin Hahmann, Stefan Schneider, T. Zwick
As the technology of automated driving progresses, the market penetration and the functional importance of automotive radar systems are on the rise. Multiple access interference (crosstalk) between automotive radars will occur more often, reducing the detection capabilities of radars. The consequences are particularly critical regarding upcoming new requirements, such as the detection of small static targets in the road by radar. This Paper investigates the performance reduction of front mounted digital beamforming (DBF) radars due to the presence of an incoherent interferer on the neighboring track. A model for the estimation of signal-to-noise-ratio-loss due to crosstalk is introduced, focusing the impact of interference periods and quantities on chirp sequence radars. Further, the influence of digital beamforming is taken into account. A worst-case analysis regarding the relative position of the interferer is performed.
{"title":"Estimation of the Influence of Incoherent Interference on the Detection of Small Obstacles with a DBF Radar","authors":"Konstantin Hahmann, Stefan Schneider, T. Zwick","doi":"10.1109/ICMIM.2019.8726535","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726535","url":null,"abstract":"As the technology of automated driving progresses, the market penetration and the functional importance of automotive radar systems are on the rise. Multiple access interference (crosstalk) between automotive radars will occur more often, reducing the detection capabilities of radars. The consequences are particularly critical regarding upcoming new requirements, such as the detection of small static targets in the road by radar. This Paper investigates the performance reduction of front mounted digital beamforming (DBF) radars due to the presence of an incoherent interferer on the neighboring track. A model for the estimation of signal-to-noise-ratio-loss due to crosstalk is introduced, focusing the impact of interference periods and quantities on chirp sequence radars. Further, the influence of digital beamforming is taken into account. A worst-case analysis regarding the relative position of the interferer is performed.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726668
Chun-Lin Lu, Yichao Yuan, C. Tseng, C. Wu
This paper presents a motion detection radar sensor using metamaterial (MTM) leaky wave antennas (LWAs) operating in the 24 GHz band. Utilizing continuous-wave Doppler radar integrated with MTM LWAs to perform frequency-space mapping over the azimuth angle, we can detect multiple human motion in the indoor environments. In addition, the moving distances of different people can be obtained by analyzing the baseband signals at different carrier frequencies.
{"title":"Multi-Target Motion Detection Radar Sensor using 24GHz Metamaterial Leaky Wave Antennas","authors":"Chun-Lin Lu, Yichao Yuan, C. Tseng, C. Wu","doi":"10.1109/ICMIM.2019.8726668","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726668","url":null,"abstract":"This paper presents a motion detection radar sensor using metamaterial (MTM) leaky wave antennas (LWAs) operating in the 24 GHz band. Utilizing continuous-wave Doppler radar integrated with MTM LWAs to perform frequency-space mapping over the azimuth angle, we can detect multiple human motion in the indoor environments. In addition, the moving distances of different people can be obtained by analyzing the baseband signals at different carrier frequencies.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117219644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726704
Javier Martínez García, Robert Prophet, Juan Carlos Fuentes Michel, R. Ebelt, M. Vossiek, Ingo Weber
We introduce a method to classify ghost moving detections in automotive radar sensors for advanced driver assistance systems. A fully connected network is used to distinguish between real and false moving detections in the occupancy gridmaps. By using this architecture, we combine the local Doppler information, along with the spatial context of the surrounding scenario to classify the moving detections. A proof of concept experiment shows promising results with data from a test drive in an urban scenario.
{"title":"Identification of Ghost Moving Detections in Automotive Scenarios with Deep Learning","authors":"Javier Martínez García, Robert Prophet, Juan Carlos Fuentes Michel, R. Ebelt, M. Vossiek, Ingo Weber","doi":"10.1109/ICMIM.2019.8726704","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726704","url":null,"abstract":"We introduce a method to classify ghost moving detections in automotive radar sensors for advanced driver assistance systems. A fully connected network is used to distinguish between real and false moving detections in the occupancy gridmaps. By using this architecture, we combine the local Doppler information, along with the spatial context of the surrounding scenario to classify the moving detections. A proof of concept experiment shows promising results with data from a test drive in an urban scenario.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115365486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726661
Alexander Kaineder, O. Lang, R. Feger, Paul Dollhäubl, A. Stelzer, Stefan Leitner
This paper describes a prototype sensor for the measurement of the casting powder thickness in a continuous cast system. The sensor is realized with an conventional vector network analyzer connected to a broadband horn antenna via a coaxial cable. The radiated power is diverted to the mold by a parabolic reflector. The system operates as a frequency-stepped continuous-wave radar, delivering the complex reflection coefficient at the calibration plane. The frequency is swept from 10 GHz to 40 GHz within 500 ms. The data transfer, evaluation and visualization is done in real-time.
{"title":"Casting Powder Thickness Field-Measurement with Ultra Wideband Radar System","authors":"Alexander Kaineder, O. Lang, R. Feger, Paul Dollhäubl, A. Stelzer, Stefan Leitner","doi":"10.1109/ICMIM.2019.8726661","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726661","url":null,"abstract":"This paper describes a prototype sensor for the measurement of the casting powder thickness in a continuous cast system. The sensor is realized with an conventional vector network analyzer connected to a broadband horn antenna via a coaxial cable. The radiated power is diverted to the mold by a parabolic reflector. The system operates as a frequency-stepped continuous-wave radar, delivering the complex reflection coefficient at the calibration plane. The frequency is swept from 10 GHz to 40 GHz within 500 ms. The data transfer, evaluation and visualization is done in real-time.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/icmim.2019.8726638
{"title":"ICMIM 2019 Technical Program Committee","authors":"","doi":"10.1109/icmim.2019.8726638","DOIUrl":"https://doi.org/10.1109/icmim.2019.8726638","url":null,"abstract":"","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726801
Nicolas Scheiner, N. Appenrodt, J. Dickmann, B. Sick
Annotating automotive radar data is a difficult task. This article presents an automated way of acquiring data labels which uses a highly accurate and portable global navigation satellite system (GNSS). The proposed system is discussed besides a revision of other label acquisitions techniques and a problem description of manual data annotation. The article concludes with a systematic comparison of conventional hand labeling and automatic data acquisition. The results show clear advantages of the proposed method without a relevant loss in labeling accuracy. Minor changes can be observed in the measured radar data, but the so introduced bias of the GNSS reference is clearly outweighed by the indisputable time savings. Beside data annotation, the proposed system can also provide a ground truth for validating object tracking or other automated driving system applications.
{"title":"Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS","authors":"Nicolas Scheiner, N. Appenrodt, J. Dickmann, B. Sick","doi":"10.1109/ICMIM.2019.8726801","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726801","url":null,"abstract":"Annotating automotive radar data is a difficult task. This article presents an automated way of acquiring data labels which uses a highly accurate and portable global navigation satellite system (GNSS). The proposed system is discussed besides a revision of other label acquisitions techniques and a problem description of manual data annotation. The article concludes with a systematic comparison of conventional hand labeling and automatic data acquisition. The results show clear advantages of the proposed method without a relevant loss in labeling accuracy. Minor changes can be observed in the measured radar data, but the so introduced bias of the GNSS reference is clearly outweighed by the indisputable time savings. Beside data annotation, the proposed system can also provide a ground truth for validating object tracking or other automated driving system applications.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130310186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ICMIM.2019.8726648
Carlos Moreno Leon, M. González-Huici, T. Dallmann
One important aspect in the design of a generic radar target simulator is the level of complexity incorporated in the generation of scenarios. The trade-off between the expected fidelity in the generation of scenarios and the computational constraints in the target simulation system raises alternatives to model-based approaches. In this paper we present a data-driven method for the generation of road scenarios in the context of automotive radar target simulation. The method characterizes the scenarios relying on radar recordings and prior information on the testing set-up. The recorded data is processed in order to play back the scenario with a radar target simulator. This is relevant, for instance, so that certain functionalities of the radar under test can be evaluated and tuned in reproducible conditions. The presented data-driven method is applied to one particular road scenario and validated in simulation experiments.
{"title":"Data-driven Generation of Road Scenarios for Radar Target Simulation in Automotive Context","authors":"Carlos Moreno Leon, M. González-Huici, T. Dallmann","doi":"10.1109/ICMIM.2019.8726648","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726648","url":null,"abstract":"One important aspect in the design of a generic radar target simulator is the level of complexity incorporated in the generation of scenarios. The trade-off between the expected fidelity in the generation of scenarios and the computational constraints in the target simulation system raises alternatives to model-based approaches. In this paper we present a data-driven method for the generation of road scenarios in the context of automotive radar target simulation. The method characterizes the scenarios relying on radar recordings and prior information on the testing set-up. The recorded data is processed in order to play back the scenario with a radar target simulator. This is relevant, for instance, so that certain functionalities of the radar under test can be evaluated and tuned in reproducible conditions. The presented data-driven method is applied to one particular road scenario and validated in simulation experiments.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123073290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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