Divide-and-Conquer Based Closed-form Position Estimation for AOA and TDOA Measurements

Abstract

Mobile location using Time Of Arrival (TOA), Time Difference Of Arrival (TDOA) or Angle Of Arrival (AOA) measurements has received considerable attention over the last years. Several closed-form algorithms have been presented for the TOA and TDOA case based on approximations of the Maximum-Likelihood (ML) estimator. In the case of AOA measurements, only ad-hoc estimators have been presented in order to avoid the classical linearization solution that needs an initial guess. This paper presents an approximation of the ML position estimator based on AOA measurements applying the Divide-And-Conquer approach dividing the ML estimation in smaller problems lems each one with a closed-form solution. Numerical simulations show that the proposed algorithm outperforms the previous contributions and presents a generic way to combine AOA and TDOA measurements.