Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Fabian Roos"'
Autor:
Fabian Roos, Johannes Schlichenmaier, Benedikt Meinecke, Claudia Vasanelli, Christian Waldschmidt, Philipp Hugler, Maximilian Steiner, Andre Durr
Publikováno v:
IEEE Antennas and Propagation Magazine. 62:34-45
Have you read everything about direction-of-arrival estimation in textbooks but are still uncertain how to realize it in practice? This tutorial-like article will help to link the theory with a practical approach for direction-of-arrival estimation u
Autor:
Stephan Hafner, Martin Hitzler, Fabian Roos, Martin Geiger, Reiner Thoma, Andre Durr, Philipp Hugler, Dominik Schwarz, Christian Waldschmidt
Publikováno v:
IEEE Transactions on Microwave Theory and Techniques. 67:3897-3907
A high-resolution frequency-modulated continuous wave imaging radar for short-range applications is presented. A range resolution of about 1 cm is achieved with a bandwidth of up to 16 GHz around 160 GHz. In order to overcome losses and large toleran
Publikováno v:
2020 IEEE Radar Conference (RadarConf20).
Since the number of radar sensors per vehicle has been increasing in order to improve the performance of Advanced Driver Assistance Systems, mutual interference has become one of the most important challenges for near future automotive radar systems.
Publikováno v:
IEEE Microwave Magazine. 19:43-53
Modern consumer and industrial unmanned aerial vehicles (UAVs) are easy-to-use flying sensor platforms. They offer stable flight, good maneuverability, hovering, and even waypoint flights in autopilot mode. For stabilization and localization, sensors
Autor:
Benedikt Meinecke, Claudia Vasanelli, Thomas Zwick, Philipp Hugler, Jonathan Mayer, Christian Waldschmidt, Fabian Roos, Omar Elsayad
Publikováno v:
2019 International Conference on Electromagnetics in Advanced Applications (ICEAA).
In a number of applications millimeter-wave multiple-input multiple-output (MIMO) radars are widely employed. The use of conformal antenna arrays has been recently proposed to improve the radar sensor performance. This paper presents an optimization
Publikováno v:
2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM).
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 amon
In many applications, the direction of arrival (DoA) information of the radar signal plays a decisive role in target localization. A multiple-input multiple-output (MIMO) radar allows to obtain the position of an object in space within one measuremen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95916069b0162eb20f942022120025f4
Autor:
Christian Waldschmidt, Patrik Gruner, Philipp Hugler, Dominik Schwarz, Andre Durr, Fabian Roos, Stephan Bucher
Publikováno v:
Scopus-Elsevier
The multiple-input and multiple-output (MIMO) principle is a well-established method to improve the angular resolution of radars. Due to hardware limitations the maximum number of transmit and receive channels is often limited. In order to further in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e86708400d7025a9886fcad41b0641ae
The topic of autonomous driving currently draws much media attention, and automobile manufacturers and component suppliers are working on the realisation of autonomous vehicles. On the way to a fully autonomously driving vehicle, different levels of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::497a71b19858f9e7f6578c1e6d39f272
Autor:
Muhammad Ahsan Razzaq, Jonathan Bechter, Jurgen Dickmann, Christian Waldschmidt, Nils Appenrodt, Fabian Roos, Philipp Hugler, Christina Knill
Publikováno v:
RWS
The application of iterative compressed sensing algorithms for automotive radar is often considered as too complex for real-time evaluation. In this paper, it is shown that the number of required iterations can be chosen considerable low. To determin