Symmetric Nested MIMO Architecture for Mixed Far-Field and Near-Field Source Localization

Recently, there has been an increasing interest in sparse multiple-input multiple-output (MIMO) architectures due to their enhanced degrees of freedom and reduced mutual coupling compared to uniform MIMO architectures. In this paper, we devise a symmetric double nested MIMO array (SDNMA) for mixed far-field and near-field (NF) source localization. The SDNMA architecture consists of one dense uniform linear array (ULA) and two sparse ULAs, where the dense ULA is used as the transmit array, two sparse ULAs and the sensor at the center form the receive array. Moreover, both the transmit and receive arrays constitute a symmetric double nested array. Under the given number of sensors, the SDNMA architecture is expressed in a closed-form and its contiguous lag ranges in the difference coarray of sum coarray can be analytically given. Additionally, we derive the optimum SDNMA architecture by maximizing the number of contiguous lags Compared with the existing MIMO arrays, the SDNMA achieves more contiguous coarray lags and a larger sum coarray aperture under the fixed total number of sensors. Numerical results show that the SDNMA achieves better localization performance than several known symmetric MIMO arrays.