Moving targets TDOA/FDOA passive localization algorithm based on localization error refinement
LIU Yang1, YANG Le1,2, GUO Fucheng1, JIANG Wenli1
1. College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;
2. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
For the two-stage weighted least squares (TSWLS) technique of passive source localization using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements, which has the problem that the root mean square error (RMSE) and localization bias is large as the measurement noise increases. Based on analyzing the factor influencing the performances of the TSWLS firstly and then improves the TSWLS via Taylor-series (TS) expansion technique. The first stage of the new algorithm is the same as the one of TSWLS. At the second stage of the new algorithm, the localization error of the first stage is identified through utilizing the first-order Taylor-series expansion. Through updating the first-stage localization error, the final localization output is obtained. Theoretical performance analysis shows that the proposed estimator can attain the Cramer-Rao lower bound (CRLB) accuracy. Computer simulations are used to contrast the new technique with the TSWLS algorithm, the iterative maximum likelihood method based on TS and the constrained total least squares (CTLS) algorithm in terms of their localization RMSE and the localization bias. The new algorithm whose complexity is almost the same as TSWLS, the RMSE and localization bias are lower than TSWLS, TS and CTLS algorithm.
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