RIS-ADMM: A RIS and ADMM-Based Passive and Sparse Sensing Method With Interference Removal
This work addresses passive sensing for radar and wireless communication domains, offering an incremental improvement over existing methods.
The paper tackles passive sensing using wireless signals and Reconfigurable Intelligent Surfaces (RIS) in the presence of interference, proposing a RIS-ADMM method that improves direction of arrival (DOA) estimation accuracy with low computational complexity.
Reconfigurable Intelligent Surfaces (RIS) emerge as promising technologies in future radar and wireless communication domains. This letter addresses the passive sensing issue utilizing wireless communication signals and RIS amidst interference from wireless access points (APs). We introduce an atomic norm minimization (ANM) approach to leverage spatial domain target sparsity and estimate the direction of arrival (DOA). However, the conventional semidefinite programming (SDP)-based solutions for the ANM problem are complex and lack efficient realization. Consequently, we propose a RIS-ADMM method, an innovative alternating direction method of multipliers (ADMM)-based iterative approach. This method yields closed-form expressions and effectively suppresses interference signals. Simulation outcomes affirm that our RIS-ADMM method surpasses existing techniques in DOA estimation accuracy while maintaining low computational complexity. The code for the proposed method is available online \url{https://github.com/chenpengseu/RIS-ADMM.git}.