Research And Realization On Time Difference Estimation And Location Algorithm In Passive Location

With the constant development of modern electronic technology, passive location technology has become more and more attractive since it has many advantages, such as good concealment, enhancing the anti-reconnaissance and anti-interference ability of the system. And the passive location technology based on time difference of arrival(TDOA) have attracted more and more attention and research by many scholars, because of its high positioning accuracy, strong networking ability and low receiving system requirement.TDOA estimation and localization algorithms of passive location are studied and implemented in this paper. First of all, the traditional cross-correlation algorithm and incoherent TDOA estimation algorithm are described, and the performance of the algorithms is compared by the simulations. The explicit time delay estimation algorithm(ETDE) and explicit time delay and gain estimation algorithm(ETDGE) based on adaptive theory are studied. And aiming at the problem of the biased TDOA estimate of the two algotihms under low signal-to-noise ratio(SNR) for nonwhite signals, an improved ETDE algorithm considering noise-input is proposed. And the mixed modulated Lagrange explicit time delay estimation(MMLETDE) algorithm is studied. Also considering the noise-input, the MMLETDE algorithm is improved and an improved MMLETDE algorithm under low SNRs is presented. The performance of the improved algorithms is verified by simulations.Secondly, the classical Taylor-Series algorithm and Chan algorithm are briefly described. And the two step least square algorithm which considers the sensor position Errors is studied. The performance of algorithms is simulated under different conditions.Thirdly, the maximum likelihood direct position determination(ML-DPD) algorithm based on the TDOA/FDOA and the adaptive direct position determination algorithm based on TDOA are studied. Aiming at the dilemma of fast convergence rate or low steady-state mean-square error of ADPD algorithm, a variable step-size normalized ADPD algorithm with alternate iteration is proposed. Besides, aiming at the problem of biased position estimate of ADPD algorithm under low SNRs for nonwhite signals, an ADPD algorithm under low SNRs is also presented. The performance of the two improved algorithms is also verified through simulations.Finally, the TDOA estimation and location algorithms are implemented in this paper. The design procedure of each module in the implemented algorithms is described. The implemented TDOA estimation module and TDOA localization module are respectively tested, and the experiment results are briefly analyzed.