Research On Motive Bistatic TDOA/FDOA Localization Algorithm

Bistatic passive location technology has the advantages has a wide range of applications due to its advantages of less receiver requirement and flexible base station settings.With the development of passive location algorithms,the location algorithms under different observation systems have become more and more mature.However,the research on the application of different algorithms in Bistatic passive location scene is not perfect.This thesis studies and analyzes the location algorithm based on TDOAs and FDOAs(or Doppler frequency shifts).The main works include the following aspects:(1)This thesis investigates the research status of algorithm based on TDOAs and FDOAs(or Doppler frequency shifts),summarizes the ideas of classic algorithms,analyzes the strengths and weaknesses of different algorithms,and paves the way for the application of different algorithms in the Bistatic passive location scene.(2)The construction of model based on Bistatic scene.By analyzing the characteristics of the Bistatic TDOAs-FDOAs joint positioning system,the positioning model is established,and the Cramer&Rao Bound of positioning performance is analyzed.In order to solve the problem that the time-frequency difference between two stations at the same time is not enough to locate the moving target,This thesis uses a set of TDOA and FDOA through multiple observations in a period of time.and constructs the location model of moving target.Through simulation,reasonable observation times and observation time interval are selected to ensure the performance of the algorithm and lay a good foundation for subsequent algorithms.(3)Research on iterative algorithm based on maximum likelihood estimation.Due to the nonlinear relationship between time-frequency difference observation and parameters of motion state,it is difficult to directly solve the observation equation,so it is often necessary to approximate the problem by linearization method.This thesis studies the classical Taylor-series algorithm based on maximum likelihood estimation,and the Taylor series localization method based on multiple observations is realized.In the case of location and speed estimation error of the base station,the covariance matrix is weighted by using the prior statistical information to improve the classical Taylor series method.(4)Research on display solution based on approximate linearization method.The iterative algorithm based on maximum likelihood estimation needs a good initial estimate to ensure the performance of the algorithm.In this paper,we use the classical approximate linearization method of multi station positioning for reference,and realize the display solution of static target and moving target respectively.By expanding the redundant variables with Taylor series,the least square problem of estimation bias is constructed,which improves the accuracy of the algorithm.At the same time,the method can also be applied to the two-step weighted least square method of TDOA and Doppler frequency shift joint positioning.