Super-Resolution Radar Imaging With Sparse Arrays Using a Deep Neural Network Trained With Enhanced Virtual Data

This paper introduces a method based on a deep neural network (DNN) that is perfectly capable of processing radar data from extremely thinned radar apertures. The proposed DNN processing can provide both aliasing-free radar imaging and super-resolution. The results are validated by measuring the det...

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Egile Nagusiak:	Christian Schuessler, Marcel Hoffmann, Martin Vossiek
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	IEEE 2023-01-01
Saila:	IEEE Journal of Microwaves
Gaiak:	Neural networks super-resolution sparse antenna arrays compressed sensing self-supervised learning radar simulation
Sarrera elektronikoa:	https://ieeexplore.ieee.org/document/10175032/
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