An efficient solution for locating a target was proposed, which by using time difference of arrival （TDOA） measurements in the presence of random sensor position errors to increase the accuracy of estimation. The ca...An efficient solution for locating a target was proposed, which by using time difference of arrival （TDOA） measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares （TSWLS） method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares （WLS）. The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound （CRLB） easily and effectively improve the localization accuracy.展开更多
基金supported by the National Natural Science Foundation of China (61271236, 61601245)the Open Research Program of the State Key Laboratory of Millimeter Waves (K201724)the China Postdoctoral Science Foundation Funded Project (2016M601693)
文摘An efficient solution for locating a target was proposed, which by using time difference of arrival （TDOA） measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares （TSWLS） method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares （WLS）. The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound （CRLB） easily and effectively improve the localization accuracy.
