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In this paper, we investigate the problem of estimating the position and theangle of rotation of a mobile station (MS) in a millimeter wave (mmWave)multiple-input-multiple-output (MIMO) system aided by a reconfigurableintelligent surface (RIS). The virtual line-of-sight (VLoS) link created by theRIS and the non-line-of-sight (NLoS) links that originate from scatterers inthe considered environment are utilized to facilitate the estimation. Atwo-step positioning scheme is exploited, where the channel parameters arefirst acquired, and the position-related parameters are then estimated. Thechannel parameters are obtained through a coarser and a subsequent finerestimation processes. As for the coarse estimation, the distributed compressedsensing orthogonal simultaneous matching pursuit (DCS-SOMP) algorithm, themaximum likelihood (ML) algorithm, and the discrete Fourier transform (DFT) areutilized to separately estimate the channel parameters. The obtained channelparameters are then jointly refined by using the space-alternating generalizedexpectation maximization (SAGE) algorithm, which circumvents thehigh-dimensional optimization issue of ML estimation. Departing from theestimated channel parameters, the positioning-related parameters are estimated.The performance of estimating the channel-related and position-relatedparameters is theoretically quantified by using the Cramer-Rao lower bound(CRLB). Simulation results demonstrate the superior performance of the proposedpositioning algorithms.

RIS-Position and Orientation Estimation in MIMO-OFDM Systems with Practical Scatterers