6 papers · 1 filter
Single-Snapshot Localization Using Sparse Extremely Large Aperture Arrays
Yunqiao Hu, Xuesu Xiao, Steven Jones +1
This paper investigates single-snapshot direction-of-arrival (DOA) estimation and target localization with coherent sparse extremely large aperture arrays (ELAAs) in automotive rad…
Model-Based Learning for DOA Estimation with One-Bit Single-Snapshot Sparse Arrays
Yunqiao Hu, Shunqiao Sun, Yimin D. Zhang
We address the challenging problem of estimating the directions-of-arrival (DOAs) of multiple off-grid signals using a single snapshot of one-bit quantized measurements. Convention…
Enhancing Off-Grid One-Bit DOA Estimation with Learning-Based Sparse Bayesian Approach for Non-Uniform Sparse Array
Yunqiao Hu, Shunqiao Sun, Yimin D. Zhang
This paper tackles the challenge of one-bit off-grid direction of arrival (DOA) estimation in a single snapshot scenario based on a learning-based Bayesian approach. Firstly, we fo…
Collaborative Automotive Radar Sensing via Mixed-Precision Distributed Array Completion
Arian Eamaz, Farhang Yeganegi, Yunqiao Hu +2
This paper investigates the effects of coarse quantization with mixed precision on measurements obtained from sparse linear arrays, synthesized by a collaborative automotive radar…
Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion
Arian Eamaz, Farhang Yeganegi, Yunqiao Hu +2
The design of sparse linear arrays has proven instrumental in the implementation of cost-effective and efficient automotive radar systems for high-resolution imaging. This paper in…
IHT-Inspired Neural Network for Single-Snapshot DOA Estimation with Sparse Linear Arrays
Yunqiao Hu, Shunqiao Sun
Single-snapshot direction-of-arrival (DOA) estimation using sparse linear arrays (SLAs) has gained significant attention in the field of automotive MIMO radars. This is due to the…