5 citations · 7 across the 6 of their papers we have counts for
6 papers
Deep Frequency Attention Networks for Single Snapshot Sparse Array Interpolation
Ruxin Zheng, Shunqiao Sun, Hongshan Liu
Sparse arrays have been widely exploited in radar systems because of their advantages in achieving large array aperture at low hardware cost, while significantly reducing mutual co…
Advancing Single-Snapshot DOA Estimation with Siamese Neural Networks for Sparse Linear Arrays
Ruxin Zheng, Shunqiao Sun, Hongshan Liu +1
Single-snapshot signal processing in sparse linear arrays has become increasingly vital, particularly in dynamic environments like automotive radar systems, where only limited snap…
Redefining Automotive Radar Imaging: A Domain-Informed 1D Deep Learning Approach for High-Resolution and Efficient Performance
Ruxin Zheng, Shunqiao Sun, Holger Caesar +2
Millimeter-wave (mmWave) radars are indispensable for perception tasks of autonomous vehicles, thanks to their resilience in challenging weather conditions. Yet, their deployment i…
Antenna Failure Resilience: Deep Learning-Enabled Robust DOA Estimation with Single Snapshot Sparse Arrays
Ruxin Zheng, Shunqiao Sun, Hongshan Liu +3
Recent advancements in Deep Learning (DL) for Direction of Arrival (DOA) estimation have highlighted its superiority over traditional methods, offering faster inference, enhanced s…
Interpretable and Efficient Beamforming-Based Deep Learning for Single Snapshot DOA Estimation
Ruxin Zheng, Shunqiao Sun, Hongshan Liu +2
We introduce an interpretable deep learning approach for direction of arrival (DOA) estimation with a single snapshot. Classical subspace-based methods like MUSIC and ESPRIT use sp…
Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving
Ruxin Zheng, Shunqiao Sun, David Scharff +1
The potentials of automotive radar for autonomous driving have not been fully exploited. We present a multi-input multi-output (MIMO) radar transmit and receive signal processing c…