Semidefinite programming approach for source localization using TDOA, FDOA and AOA measurements

Abstract

The position and velocity of a moving source can be located by multiple geometrical separated sensors using the hybrid time difference of arrival (TDOA), frequency difference of arrival (FDOA), and angle of arrival (AOA). For the case where the TDOA measurement is more precise than the AOA measurement, this paper proposes a passive localization method based on a semidefinite relaxation technique (SDR). The localization problem is first transformed into a constrained weighted least-squares problem through pseudo linearization, then converted to convex semidefinite programming (SDP) problem using the semidefinite relaxation technique. Simulation results indicate that the proposed method can achieve Cramer-Rao lower bound (CRLB) at moderate noise levels and achieves a significant performance improvement over previous methods.