Training of deep neural networks using radar measurements made with varying waveform settings
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TNO
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Den Haag, Netherlands, Europe

The goal of this assignment is to investigate how radar measurements made with varying waveform settings can be used for training a deep neural network for target classification. One possible approach is the investigation into the use of data representations that are independent of the radar waveform settings, such that the input to the neural network is consistent. Another possible approach is the investigation into neural network architectures that are robust with respect to varying waveform settings. Radar measurements with varying waveform settings are available for this assignment. You will perform this assignment in the Department of Radar Technology. We are a passionate and creative group of professionals (60 people) dedicated to the specification, development and evaluation of innovative, high-performance MMICs, miniaturised and integrated RF subsystems, antennas and front-ends. The department is at the heart of novel, game-changing radar system and signal processing concepts for the military, space and civil domains.

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