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20162024
most citedCompressed sensing radar detectors under the row-orthogonal design model: a statistical mechanics perspective

8 citations · 17 across the 12 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

eess.SP2021

Theoretical Linear Convergence of Deep Unfolding Network for Block-Sparse Signal Recovery

Rong Fu, Vincent Monardo, Tianyao Huang +1

In this paper, we consider the recovery of the high-dimensional block-sparse signal from a compressed set of measurements, where the non-zero coefficients of the recovered signal o…

eess.SP2021

Block-Sparse Recovery Network for Two-Dimensional Harmonic Retrieval

Rong Fu, Tianyao Huang, Lei Wang +1

As a typical signal processing problem, multidimensional harmonic retrieval (MHR) has been adapted to a wide range of applications in signal processing. Block-sparse signals, whose…

eess.SP2021★ 4 cited

Transmit Design for Joint MIMO Radar and Multiuser Communications with Transmit Covariance Constraint

Xiang Liu, Tianyao Huang, Yimin Liu

In this paper, we consider the design of a multiple-input multiple-output (MIMO) transmitter which simultaneously functions as a MIMO radar and a base station for downlink multiuse…

eess.SP2021

FRaC: FMCW-Based Joint Radar-Communications System via Index Modulation

Dingyou Ma, Nir Shlezinger, Tianyao Huang +2

Dual function radar communications (DFRC) systems are attractive technologies for autonomous vehicles, which utilize electromagnetic waves to constantly sense the environment while…

cs.RO2021★ 2 cited

Are We Ready for Unmanned Surface Vehicles in Inland Waterways? The USVInland Multisensor Dataset and Benchmark

Yuwei Cheng, Mengxin Jiang, Jiannan Zhu +1

Unmanned surface vehicles (USVs) have great value with their ability to execute hazardous and time-consuming missions over water surfaces. Recently, USVs for inland waterways have…

eess.SP2021

Structured LISTA for Multidimensional Harmonic Retrieval

Rong Fu, Yimin Liu, Tianyao Huang +1

Learned iterative shrinkage thresholding algorithm (LISTA), which adopts deep learning techniques to learn optimal algorithm parameters from labeled training data, can be successfu…