Direct position determination based on unitary space-time subspace data fusion

Abstract

Direct position determination (DPD) is a single-step method which directly localizes transmitters from sensor outputs without computing intermediate parameters. Compared with conventional two-step localization methods, DPD achieves higher accuracy especially under low signal to noise ratio (SNR) conditions. This paper proposes an improved subspace data fusion (SDF)-based DPD algorithm with a moving array. Different from the existing SDF-based DPD which uses only the arrival angle information, the proposed algorithm exploits the location information embedded in both arrival angles and Doppler shifts. It relies on a unitary space-time SDF, where multiple stationary transmitters are directly localized by fusing all the unitary (real-valued) space-time subspaces at all positions of the moving array. Therefore, our algorithm realizes the localization by real-valued computations. The simulation results show the superior localization performance of the proposed DPD compared to the existing SDF-based DPD and two-step localization algorithms.