Uplink Sensing with Unknown Transmitter Position in Clutter Environment via Tensor Decomposition

To support emerging smart applications, joint communication and sensing (JCAS) integrates sensing into communications to save resources and provide a wider sensing service. Although there have been many works in this area, almost all of them are based on the sometimes impractical assumption that the position of the transmitter is known. In this paper, we propose a low-complexity multi-target-aided method for uplink MIMOOFDM sensing in a cluttered environment with an unknown transmitter's position. Specially, we form the signal received at the base station (BS) as a fourth-order tensor, and after clutter suppression, we adopt a low-rank CANDECOMP/PARAFAC (CP) decomposition to perform parameter estimations. Through theory analysis, our CP decomposition satisfies the condition of uniqueness. Simulation results show that the proposed method can achieve better normalized mean square error performance than the existing methods and even approach a similar performance with the ideal case benchmark.