3 citations · 6 across the 14 of their papers we have counts for
4 papers · 1 filter
Deep Learning-Enabled One-Bit DoA Estimation
Farhang Yeganegi, Arian Eamaz, Tara Esmaeilbeig +1
Unrolled deep neural networks have attracted significant attention for their success in various practical applications. In this paper, we explore an application of deep unrolling i…
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…
HDR Imaging With One-Bit Quantization
Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian
Modulo sampling and dithered one-bit quantization frameworks have emerged as promising solutions to overcome the limitations of traditional analog-to-digital converters (ADCs) and…