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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
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Distributed radar systems comprise a coherent network of spatially distributed sensors that can be independently transmitting, receiving, or both. By acting in unison, rather than in isolation
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Almost all radar systems currently transmit from the same location. A drastic departure from this sensing architecture is distributed radar – enacted by a coherent network of spatially distributed
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are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
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& Applications. The SPARC group in SnT is pursuing research on signal processing applications in radar and communication systems in partnership with national and international academic and industrial collaborators
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the design and optimization of multistatic and multifrequency radar architectures for near-field 3D imaging. - Contribute to the electromagnetic modeling of radiating systems, wave-object interaction, and
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a related field ▪ Strong knowledge in wireless communication systems, signal processing, or radar systems ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in hands
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radar topic and are you interested in a PhD position? Then this position is for you! Job description We invite applications for a fully funded PhD position focusing on advanced geodetic monitoring
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to investigate the feasibility of original applications within a VIRC, as for instance characterization of antennas (efficiency, radiation pattern) and radar-cross section measurements, over-the-air tests
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Experience with high-resolution satellite remote sensing data and geospatial processing workflows (radar and/or optical sensors are an advantage) Experience with geospatial data formats and tools (e.g., NetCDF