Abstract:

Using the time difference of arrival,frequency difference of arrival,and differential Doppler rate measurements from target radiation signals received by multiple receivers for joint localization is a current research hotspot as it can effectively enhance the passive location accuracy of moving targets.However,existing algorithms commonly employ a two-step weighted least squares method,which often results in significant positioning errors in low signal-to-noise ratio environments.To address this issue,a semidefinite relax method for moving targets localization is proposed.This method en-compasses three steps:first,by introducing three auxiliary variables,a pseudolinear passive location equation set is constructed; second,the localization problem is transformed into a quadratic pro-gramming problem with quadratic constraints by leveraging the relationship between the auxiliary variables and the target localization solution; finally,the semidefinite relaxation method is employed to convert the quadratic constraint optimization into a convex optimization problem,which is efficiently solved using optimization toolboxes.Simulation results demonstrate that,compared with the existing methods,the signal-to-noise ratio required by the proposed algorithm to achieve the target localization accuracy of the Cramer-Rao Lower Bound is smaller by at least 9 dB,and the proposed algorithm has a smaller localization error in lower signal-to-noise ratio environment.The effectiveness of the pro-posed algorithm is proved.

Key words: source localization, time difference of arrival, frequency difference of arrival, differential Doppler rate, semidefinite relax