Pub Date : 2019-06-03DOI: 10.1109/ICMIM.2019.8726765
J. Schlichenmaier, Fabian Roos, Philipp Hügler, C. Waldschmidt
As high resolution automotive radars become more common, so does their usage for next-generation functionalities like advanced driver assistant systems and autonomous driving. This creates the need for robust clustering techniques to distinguish among multiple extended objects like vehicles in the same scenario. One especially challenging scenario is that of separating two extended targets close to each other, each following its own trajectory. This paper proposes a clustering algorithm based on the analysis of the velocity profile to divide target points of multiple vehicles into sub-clusters. The theoretical background is explained and shown on simulation data. The algorithm is verified using radar measurements of two extended vehicular targets.
{"title":"Clustering of Closely Adjacent Extended Objects in Radar Images using Velocity Profile Analysis","authors":"J. Schlichenmaier, Fabian Roos, Philipp Hügler, C. Waldschmidt","doi":"10.1109/ICMIM.2019.8726765","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726765","url":null,"abstract":"As high resolution automotive radars become more common, so does their usage for next-generation functionalities like advanced driver assistant systems and autonomous driving. This creates the need for robust clustering techniques to distinguish among multiple extended objects like vehicles in the same scenario. One especially challenging scenario is that of separating two extended targets close to each other, each following its own trajectory. This paper proposes a clustering algorithm based on the analysis of the velocity profile to divide target points of multiple vehicles into sub-clusters. The theoretical background is explained and shown on simulation data. The algorithm is verified using radar measurements of two extended vehicular targets.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124608627","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 : 2019-04-15DOI: 10.1109/ICMIM.2019.8726843
Soumya Krishnapuram Sireesh, Sanaz Hadipour Abkenar, N. Christoffers, C. Wagner, A. Stelzer
The frequency chirps applied in frequency modulated continuous wave (FMCW) radars are typically generated using a PLL imposing trade-offs between noise and modulation accuracy. We are removing this compromise by employing a fixed frequency PLL, direct digital chirps generation and up-conversion to RF using an RFDAC. With a simplified PLL requirement and better exploitation of nm-scale CMOS digital performance, we achieve lower noise, less chip area, and frequency error, and remove the issues with frequency ramp non-linearities in conventional FMCW architectures.
{"title":"Direct Digital Modulation and RFDAC for Generation of Frequency Ramps in FMCW Radar","authors":"Soumya Krishnapuram Sireesh, Sanaz Hadipour Abkenar, N. Christoffers, C. Wagner, A. Stelzer","doi":"10.1109/ICMIM.2019.8726843","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726843","url":null,"abstract":"The frequency chirps applied in frequency modulated continuous wave (FMCW) radars are typically generated using a PLL imposing trade-offs between noise and modulation accuracy. We are removing this compromise by employing a fixed frequency PLL, direct digital chirps generation and up-conversion to RF using an RFDAC. With a simplified PLL requirement and better exploitation of nm-scale CMOS digital performance, we achieve lower noise, less chip area, and frequency error, and remove the issues with frequency ramp non-linearities in conventional FMCW architectures.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125148148","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 : 2019-04-15DOI: 10.1109/ICMIM.2019.8726699
Maximilian Steiner, Timo Grebner, C. Waldschmidt
Networks of distributed sensors in automotive applications enable the coverage of wide areas of the surrounding. The spacing between multiple sensors, that observe a common scene, provides different views on jointly detected targets. In this paper, a moving vehicle with multiple single-channel radar sensors is used to create a high-resolution image. The proposed approach is based on a single chirp-sequence measurement of multiple radars. It utilizes a joint radar ego-motion estimation to compensate the motion of the vehicle whereby it is possible to generate an image. Thus, this approach is independent of external systems for the motion compensation like global satellite navigation systems. Measurements at 77GHz with 5 sensors are conducted to demonstrate the performance in an automotive scenario.
{"title":"Chirp-Sequence-Based Imaging Using a Network of Distributed Single-Channel Radar Sensors","authors":"Maximilian Steiner, Timo Grebner, C. Waldschmidt","doi":"10.1109/ICMIM.2019.8726699","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726699","url":null,"abstract":"Networks of distributed sensors in automotive applications enable the coverage of wide areas of the surrounding. The spacing between multiple sensors, that observe a common scene, provides different views on jointly detected targets. In this paper, a moving vehicle with multiple single-channel radar sensors is used to create a high-resolution image. The proposed approach is based on a single chirp-sequence measurement of multiple radars. It utilizes a joint radar ego-motion estimation to compensate the motion of the vehicle whereby it is possible to generate an image. Thus, this approach is independent of external systems for the motion compensation like global satellite navigation systems. Measurements at 77GHz with 5 sensors are conducted to demonstrate the performance in an automotive scenario.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134039622","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 : 2019-04-15DOI: 10.1109/ICMIM.2019.8726509
Karim Ishak, Z. Zafar, Maximilian Steiner, N. Appenrodt, J. Dickmann, C. Waldschmidt
Human gestures and movements recognition is becoming an indispensable task in today’s world for many ranges of applications. For example, radar sensors are of big interest in the automotive industry due to its many advantages such as the ability to work in various weather conditions beside performing during night as well as during daytime. A ground truth system would be advantageous in labelling and obtaining more details of the measured scenarios. In this paper, a measurement setup with a ground truth system using Kinect is going to be used. Processing of the data obtained from Kinect proves to be helpful in getting more information about the performed gestures. The synchronization between Kinect and radar is also an important issue, which is performed here on a hardware level to minimize the delays from the software level. In a world where deep learning is increasingly used in various aspects of life, having more synchronized data points from Kinect beside the ones from the radar is also needed.
{"title":"A Radar Measurement Setup with a Ground Truth System for Micro-Doppler Human Movements","authors":"Karim Ishak, Z. Zafar, Maximilian Steiner, N. Appenrodt, J. Dickmann, C. Waldschmidt","doi":"10.1109/ICMIM.2019.8726509","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726509","url":null,"abstract":"Human gestures and movements recognition is becoming an indispensable task in today’s world for many ranges of applications. For example, radar sensors are of big interest in the automotive industry due to its many advantages such as the ability to work in various weather conditions beside performing during night as well as during daytime. A ground truth system would be advantageous in labelling and obtaining more details of the measured scenarios. In this paper, a measurement setup with a ground truth system using Kinect is going to be used. Processing of the data obtained from Kinect proves to be helpful in getting more information about the performed gestures. The synchronization between Kinect and radar is also an important issue, which is performed here on a hardware level to minimize the delays from the software level. In a world where deep learning is increasingly used in various aspects of life, having more synchronized data points from Kinect beside the ones from the radar is also needed.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"38 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113986272","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.2019.8726554
Jonas Fuchs, R. Weigel, M. Gardill
An alternative approach to high-resolution direction-of-arrival estimation in the context of automotive FMCW signal processing is shown by training a neural network with simulation as well as experimental data to estimate the mean and distance of the azimuth angles from two targets. Testing results are post-processed to obtain the estimated azimuth angles which can be validated afterwards. The performance of the proposed neural network is then compared with a reference implementation of a maximum likelihood estimator. Final evaluations show super-resolution like performance with significantly reduced computation time, which is expected to have an impact on future multi-dimensional high-resolution DoA estimation.
{"title":"Single-Snapshot Direction-of-Arrival Estimation of Multiple Targets using a Multi-Layer Perceptron","authors":"Jonas Fuchs, R. Weigel, M. Gardill","doi":"10.1109/ICMIM.2019.8726554","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726554","url":null,"abstract":"An alternative approach to high-resolution direction-of-arrival estimation in the context of automotive FMCW signal processing is shown by training a neural network with simulation as well as experimental data to estimate the mean and distance of the azimuth angles from two targets. Testing results are post-processed to obtain the estimated azimuth angles which can be validated afterwards. The performance of the proposed neural network is then compared with a reference implementation of a maximum likelihood estimator. Final evaluations show super-resolution like performance with significantly reduced computation time, which is expected to have an impact on future multi-dimensional high-resolution DoA estimation.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"61 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":"115534670","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.2019.8726797
Jiahao Zhang, S. Yan, G. Vandenbosch
In order to satisfy modern diverse communication requirements, a low-profile frequency reconfigurable antenna with polarization and pattern diversity is proposed. Two different metamaterial inspired reconfigurable structures are designed and integrated in a single antenna. The so-called 1 mode of an outer annular right/left-handed transmission line (CRLH-TL) based radiator provides a broadside radiation pattern. The so-called 0 mode of an inner circular radiator loaded with split ring resonators (SRRs) provides an omni-directional radiation pattern. Polarization and pattern diversity are thus achieved. These two radiators are continuously tuned with varactors to realize frequency reconfigurability in a tuning range from 1.7 GHz to 2.2 GHz. The antenna has a low profile of 0.042 λ. For demonstration, a prototype antenna is implemented. Simulations and experiments match well.
{"title":"A Low-Profile Frequency Reconfigurable Antenna with Polarization and Pattern Diversity","authors":"Jiahao Zhang, S. Yan, G. Vandenbosch","doi":"10.1109/ICMIM.2019.8726797","DOIUrl":"https://doi.org/10.1109/ICMIM.2019.8726797","url":null,"abstract":"In order to satisfy modern diverse communication requirements, a low-profile frequency reconfigurable antenna with polarization and pattern diversity is proposed. Two different metamaterial inspired reconfigurable structures are designed and integrated in a single antenna. The so-called 1 mode of an outer annular right/left-handed transmission line (CRLH-TL) based radiator provides a broadside radiation pattern. The so-called 0 mode of an inner circular radiator loaded with split ring resonators (SRRs) provides an omni-directional radiation pattern. Polarization and pattern diversity are thus achieved. These two radiators are continuously tuned with varactors to realize frequency reconfigurability in a tuning range from 1.7 GHz to 2.2 GHz. The antenna has a low profile of 0.042 λ. For demonstration, a prototype antenna is implemented. Simulations and experiments match well.","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"1 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":"129761666","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.2019.8726754
{"title":"ICMIM 2019 Index","authors":"","doi":"10.1109/icmim.2019.8726754","DOIUrl":"https://doi.org/10.1109/icmim.2019.8726754","url":null,"abstract":"","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":"115334546","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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