Near-field joint estimation of multi-targets’ position and velocity in a terahertz MIMO-OFDM system based on tensor decomposition

This paper investigates the joint estimation of multi-targets’ position and velocity for a terahertz multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system operating in the near field based on tensor decomposition. The waveforms transmitted from shared antennas carry communication messages and are orthogonal to each other in the frequency domain. The estimation of the position and velocity of multiple targets in the considered near-field scenario is challenging because it involves spherical wavefronts. A signal model based on spherical wavefronts enables higher resolution on spatial position, which, if properly designed, can be used to improve the estimation accuracy. In this paper, we propose a CANDE-COMP/PARAFAC (CP) decomposition-based near-field localization (CP-NFL) algorithm for the joint estimation of the position and velocity of multiple targets. In our proposed method, the received signal is expressed as a third-order tensor; based on its factor matrices we convert the original non-convex optimization problem into a convex one and solve it with CVX tools. Our analysis reveals that the uniqueness in CP decomposition can be guaranteed and the computational complexity of our proposed method is linear to the sum of the third powers of the number of sub-carriers, OFDM symbols, antennas, and targets. Numerical results show that our proposed method has a clear advantage over the existing method in terms of estimation accuracy and computational complexity.