A Novel Geometric Solution for Moving Target Localization through Multistatic Sensing in the ISAC System

This paper proposes a novel geometric solution for tracking a moving target through multistatic sensing. In contrast to existing two-step weighted least square (2SWLS) methods which use the bistatic range (BR) and bistatic range rate (BRR) measurements, the proposed method incorporates an additional direction of arrival (DOA) measurement of the target obtained from a communication receiver in an integrated sensing and communication (ISAC) system. Unlike the existing 2SWLS methods that require at least three transmitter-receiver (TX-RX) pairs to operate, the proposed algorithm can conduct location estimation with a single TX-RX pair and velocity estimation with two TX-RX pairs. Simulations reveal that the proposed method exhibits superior performance compared to existing 2SWLS methods, particularly when dealing with moderate levels of noise in DOA measurements.

Exploiting Structured Sparsity with Low Complexity Sparse Bayesian Learning for RIS-assisted MIMO Channel Estimation

As an emerging communication auxiliary technology, reconfigurable intelligent surface (RIS) is expected to play a significant role in the upcoming 6G networks. Due to its total reflection characteristics, it is challenging to implement conventional channel estimation algorithms. This work focuses on RIS-assisted MIMO communications. Although many algorithms have been proposed to address this issue, there are still ample opportunities for improvement in terms of estimation accuracy, complexity, and applicability. To fully exploit the structured sparsity of the multiple-input-multiple-output (MIMO) channels, we propose a new channel estimation algorithm called unitary approximate message passing sparse Bayesian learning with partial common support identification (UAMPSBL-PCI). Thanks to the mechanism of PCI and the use of UAMP, the proposed algorithm has a lower complexity while delivering enhanced performance relative to existing channel estimation algorithms. Extensive simulations demonstrate its excellent performance in various environments.