F. Norouzian, E. Hoare, E. Marchetti, M. Cherniakov, M. Gashinova
{"title":"Next Generation, Low-THz Automotive Radar – the potential for frequencies above 100 GHz","authors":"F. Norouzian, E. Hoare, E. Marchetti, M. Cherniakov, M. Gashinova","doi":"10.23919/IRS.2019.8767461","DOIUrl":"https://doi.org/10.23919/IRS.2019.8767461","url":null,"abstract":"Currentautomotive radars operate under 100 GHz. The natural progression to higher frequencies beyond 100 GHz offers significant benefits in the form of increased bandwidth and exploitation of phenomena associated with shorter wavelength. Higher operating frequencies offer the possibility of significant improvement in range resolution to cm level, improving target classification, reduction in sensor size, mass cost and easier packaging of multiple sensors per vehicle. A comprehensive research program is being undertaken at the Microwave Integrated Systems Laboratory (MISL) at the University of Birmingham to quantify the advantages and limitations of operating at frequencies beyond 100 GHz for automotive applications. This paper summarizes the findings of these studies.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114499885","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}
A. Heinzel, M. Peichl, E. Schreiber, S. Dill, F. Bischeltsrieder
{"title":"The Detection Of IEDs Using Ground Based Multi-Static SAR","authors":"A. Heinzel, M. Peichl, E. Schreiber, S. Dill, F. Bischeltsrieder","doi":"10.23919/IRS.2019.8768100","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768100","url":null,"abstract":"The detection and localization of thin wires is still a challenging task. Objects like improvised explosive devices (IEDs) consist of thin wires that can not be seen by optical systems. Multi-static synthetic aperture radar (SAR) is a suitable tool to detect these wires from a safe standoff distance.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008181","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}
J. Bredemeyer, Karsten Schubert, Jens Werner, T. Schrader, M. Mihalachi
{"title":"Comparison of principles for measuring the reflectivity values from wind turbines","authors":"J. Bredemeyer, Karsten Schubert, Jens Werner, T. Schrader, M. Mihalachi","doi":"10.23919/IRS.2019.8768171","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768171","url":null,"abstract":"The radar echo of a large wind turbine (WT) is investigated in the C band: An unmanned aerial system (UAS) is used to perform a reflectivity measurement across the flight altitude using a passive bistatic radar (PBR) constellation of a non-cooperative precipitation radar transmitter in horizontal polarization. This is done at various distances to check if far field conditions apply to derive a radar cross section (RCS). As a fully independent method, a monostatic FMCW radar is installed on ground at certain distances to the WT. The results of both methods are compared against each other regarding the applicability of the RCS.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117116791","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}
Qi Yang, Chuang Yao, Hongqiang Wang, B. Deng, Yuliang Qin
{"title":"Experimental Research on Imaging of Non-rigid Targets with Micro-motion Parts in the THz Region","authors":"Qi Yang, Chuang Yao, Hongqiang Wang, B. Deng, Yuliang Qin","doi":"10.23919/IRS.2019.8768129","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768129","url":null,"abstract":"Imaging of non-rigid targets with micro-motion parts has always been a difficulty in the radar imaging field because of the complex movement, which will lead to defocusing in azimuth direction of the radar image. Compared with the traditional microwave band, the difficulty is especially serious in the terahertz region due to the Doppler sensitivity of the terahertz radar system. In this paper, experiments on imaging of a helicopter model with a 440 GHz radar system were carried out and an echo signal separation method based on the improved singular spectrum analysis was adopted. The echo signals of the micro-motion parts and the translational parts on the targets were separated excellently, thus laying a good foundation for further processing. The good focusing performance of the imaging result corresponding to the translation part verifies the effectiveness of the echo signal separation method adopted in this paper.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126121591","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}
F. Santi, F. Pieralice, D. Pastina, M. Antoniou, M. Cherniakov
{"title":"Passive radar imagery of ship targets by using navigation satellites transmitters of opportunity","authors":"F. Santi, F. Pieralice, D. Pastina, M. Antoniou, M. Cherniakov","doi":"10.23919/IRS.2019.8768131","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768131","url":null,"abstract":"This paper considers the possibility to extract features of vessels at sea with a GNSS-based passive radar system. To this purpose, a passive imaging mode has been defined to form bistatic ISAR images of the detected ship. Then, proper range and cross-range scaling factors have been derived, so that relevant features of the target such as its length can be obtained, potentially enabling target recognition procedures. Experimental results obtained with Galileo satellites demonstrate the effective possibility of the proposed approach to extract relevant features of ship targets of interest, thus providing advanced capabilities to the GNSS-based radar for maritime surveillance applications.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362320","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}
{"title":"Architecture and operational results of feature based automatic radar target classification","authors":"André Hanewinkel","doi":"10.23919/IRS.2019.8768189","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768189","url":null,"abstract":"Feature based automatic radar target classification, is a new method for classifying several types of targets based on the doppler spectrum and cepstrum, e.g. drones. This paper gives an overview over the architecture of the implemented algorithm within X-Band high-doppler resolution radar units and results concerning classification probability and ranges in different scenarios and environmental conditions.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116073438","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}
{"title":"A Concept for Far Field Measurements of Large Dimension Antennas in an Open Area Test Site Performed by UAS","authors":"Christoph Wasserzier, J. Worms, D. O’Hagan","doi":"10.23919/IRS.2019.8768157","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768157","url":null,"abstract":"Small Unmanned Aerial Systems (UAS), aka ‘Drones’, equipped with apt electromagnetic sensors open a manifold of RF applications. In the context of this paper, UAS are utilized as aerial equipment for open area test site (OATS) measurements at precise 3D locations in the far field of a ground based device under test. The advantages of UAS supported OATS measurements are addressed. The details of a prototype system are described and experimental assessments of the measurement precision are shown.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128778314","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}
{"title":"Scalable Machine Intelligence on Streaming Data With Applications for ADS-B Data","authors":"Michael Rottmaier, V. Jayakumar","doi":"10.23919/IRS.2019.8767458","DOIUrl":"https://doi.org/10.23919/IRS.2019.8767458","url":null,"abstract":"We propose an approach for self-learning, scalable systems and showcase it on a toy application based on aircraft trajectories data. Our application is to predict the position of aircrafts from its trajectory for a multi-time-horizon. Here we don’t make any assumptions on underlying kinematic models but instead ”learn” how to predict from unlabeled data describing historical aircraft trajectories, collected during system runtime.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129840787","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}
{"title":"A New Algorithm for Automatic Radar Target Classification Using Feature Extraction Having Special Regard to Drones","authors":"F. Hofele","doi":"10.23919/IRS.2019.8768116","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768116","url":null,"abstract":"The present algorithm stands for a novel method of automatic radar target classification. It specifically uses the recognition of target-typical characteristics and features of the spectrum and of the cepstrum, derived from the time-signal. In particular, the new technique allows reliable identification of the presence of drones.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116290398","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}
F. Opitz, Kaeye Dästner, Bastian von Hassler zu Roseneckh-Köhler, Elke Schmid
{"title":"Data Analytics and Machine Learning in Wide Area Surveillance Systems","authors":"F. Opitz, Kaeye Dästner, Bastian von Hassler zu Roseneckh-Köhler, Elke Schmid","doi":"10.23919/IRS.2019.8768102","DOIUrl":"https://doi.org/10.23919/IRS.2019.8768102","url":null,"abstract":"Modern surveillance networks are able to provide trajectories of all kind of vessels and aircrafts within worldwide or at least extended environment. Most widely used are Automatic Dependent Surveillance – Broadcast (ADS-B) and (Satellite-) Automatic Identification System (AIS) used within air and maritime surveillance. Both of them are cooperative systems. Besides these systems, sensor networks based on ground installations or mounted on airborne and space-based platforms deliver object trajectories independent of any cooperation. Examples include GMTI radar-based systems operating on UAV platforms and coastal or air traffic control sensor network installations. These surveillance systems provide mid- and long-term trajectories. The challenging part is the related situational awareness and the estimation of the intent of the tracked objects. New technologies include activity-based intelligence and the determination of patterns of life. An approach for these technologies can be found in the advanced analysis of those trajectories, which are extracted by the mentioned surveillance systems. Trajectories are partitioned into specific segments of interest using cluster algorithms. This helps to decode their pattern of life based on unsupervised machine learning. Trajectories are aggregated into different routes with dedicated representatives. Calculated probabilities indicate the frequentation of these routes. This allows predictive analytics and the identification of anomalous behaviour. Finally, these new data analytic techniques have to be integrated in existing near real time surveillance systems. This requires specific system architectures as well as a completely new software and hardware landscape. So, trajectory-based Machine Learning is embedded in local or global clouds and uses dedicated mechanisms for distributed and parallel processing.","PeriodicalId":155427,"journal":{"name":"2019 20th International Radar Symposium (IRS)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125996445","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}