Artificial intelligence for adaptive and reconfigurable antenna arrays: A review

F Zardi, P Nayeri, P Rocca… - IEEE Antennas and …, 2020 - ieeexplore.ieee.org
This article provides an overview of a few applications of artificial intelligence (AI) in
adaptive and reconfigurable antenna arrays. In particular, AI proves to be more robust than …

A machine learning perspective on automotive radar direction of arrival estimation

J Fuchs, M Gardill, M Lübke, A Dubey, F Lurz - IEEE access, 2022 - ieeexplore.ieee.org
Millimeter-wave sensing using automotive radar imposes high requirements on the applied
signal processing in order to obtain the necessary resolution for current imaging radar. High …

Super resolution DOA based on relative motion for FMCW automotive radar

W Zhang, P Wang, N He, Z He - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Frequency modulated continuous wave (FMCW) based millimeter wave (MMW) radar
systems have found widespread applications in advanced driving assistant system recently …

Neural-Network-Based DOA Estimation in the Presence of Non-Gaussian Interference

S Feintuch, J Tabrikian, I Bilik… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This work addresses the problem of direction-of-arrival (DOA) estimation in the presence of
non-Gaussian, heavy-tailed, and spatially-colored interference. Conventionally, the …

Coherent, super-resolved radar beamforming using self-supervised learning

I Orr, M Cohen, H Damari, M Halachmi, M Raifel… - Science Robotics, 2021 - science.org
High-resolution automotive radar sensors are required to meet the high bar of autonomous
vehicle needs and regulations. However, current radar systems are limited in their angular …

Spectrum-based single-snapshot super-resolution direction-of-arrival estimation using deep learning

M Gall, M Gardill, T Horn, J Fuchs - 2020 German Microwave …, 2020 - ieeexplore.ieee.org
A method for multi-target direction-of-arrival estimation for commercial FMCW radar systems
in the automotive domain is presented. The proposed approach realizes single-snapshot …

Deep learning based image enhancement for automotive radar trained with an advanced virtual sensor

C Schüßler, M Hoffmann, I Ullmann, R Ebelt… - IEEE …, 2022 - ieeexplore.ieee.org
This paper introduces a novel deep learning based concept for image enhancement and
distortion suppression in automotive radar signal processing. The deep neural network …

ResNet applied for a single-snapshot DOA estimation

MLL de Oliveira, MJG Bekooij - 2022 IEEE Radar Conference …, 2022 - ieeexplore.ieee.org
In this paper, we discuss the usage of Residual Neural Networks (ResNets) for calculating
the Direction Of Arrival (DOA) of MIMO radars and the estimation of the number of targets …

Tdm-mimo automotive radar point-cloud detection based on the 2-d hybrid sparse antenna array

J Ding, Z Wang, W Ma, X Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Automotive radar plays an important role in the field of advanced driver assistant systems
(ADASs), in the detection of unmanned aerial vehicles (UAV), and so on. Most automotive …

Deep-MLE: Fusion between a neural network and MLE for a single snapshot DOA estimation

MLL de Oliveira, MJG Bekooij - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
In this paper, we propose a novel framework called DeepMLE, which gives a solution to the
single-snapshot Direction Of Arrival (DOA) estimation problem, up to 4 distinct targets, using …