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Time-differences-of-arrival(TDOA) and gain-ratios-ofarrival(GROA) measurements are used to determine the passive source location. Based on the measurement models, the constrained weighted least squares(CWLS) estimator is presented.Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem(SDP), which can be solved by using modern convex optimization algorithms. Moreover,this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good performance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.
Time-differences-of-arrival (TDOA) and gain-ratios-ofarrival (GROA) measurements are used to determine the passive source location. Based on the measurement models, the constrained weighted least squares (CWLS) estimator is presented. Nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem (SDP), which can be solved by using modern convex optimization algorithms, furthermore, this relaxation can be proved to be tight, ie, the SDP solves the relaxed CWLS problem, and this prom consideration guarantees the good performance of the proposed method. furthermore, this method is extended to solve the localization problem with sensor position errors Simulation results corroborate the theoretical results and the good performance of the proposed method.