LAUSR

A robust algorithm for locating the signal source is proposed based on information fusion from different domains to improve the passive localization accuracy under the non-line-of-sight (NLoS) environment. The localization scenario is established by utilizing the information about energy domain, time domain, and frequency domain. The Cramer–Rao lower bounds are derived, and the performance improvement is proved in different domains. By substituting NLoS bias with the statistical average, the localization equations of information fusion are established. A nonconvex localization problem is transformed into a generalized trust domain subproblem by introducing the squared range and the weighted least squares. The position and velocity of the source are obtained by using the bisection procedure. An iterative method is used to estimate the NLoS deviation and refine the position accuracy simultaneously. Simulation results demonstrate the efficiency and robustness of the proposed algorithm.