Research On Multi-station Passive Localization Algorithm Based On TDOA/FDOA

In recent years,passive localization technology based on multiple receivers has been widely used in various military and civil fields,including sensor network,radar,navigation,wireless communication,etc.The parameters available for multi-station passive localization include Angel of Arrival(AOA)?Time of Arrival(TOA)?Time Difference of Arrival(TDOA)?Frequency Difference of Arrival(FDOA),etc.The positioning system combining multiple measuring parameters can combine the advantages of different parameters,and improve the positioning accuracy to a certain extent.This paper mainly studies the localization method for moving source localization based on TDOA and FDOA measurements in three-dimensional space with the unconstrained conditions.In short,the main contents of this paper are as follows:1?This paper studies and analyzes the classical two-stage Weighted Least Squares(TSWLS),this method belongs to the analytical method,which has a characteristics of simple operations and a closed solution,but its positioning accuracy is highly affected by the noise.A passive localization method is proposed based on Stochastic Robust Least Squares(SRLS)in this paper,this method regards the objective function as a new objective function to evaluate,then using the Lagrange multiplier technology to deal with constraint conditions to get a closed solution contained the Lagrange parameters.And the Newton method is used to solve Lagrange multiplier iteratively finally.This approach takes into account the possible random noise in the coefficient matrix,which is more suitable to deal with the positioning problem with randomness in the coefficient matrix compared with the methods based on Constrained Weighted Least Squares(CWLS)and Constrained Total Least Squares(CTLS).2?A two-stage Regularized Constrained Total Least Squares(TRCTLS)method is proposed in the passive localization problem based on TDOA and FDOA.This method firstly uses Regularized Constrained Total Least Squares(RCTLS)method to get a solution,unlike TSWLS method re-estimate the position and velocity of the target in the second step,this method estimates the error of the results in the first step and uses the constraints to construct a set of equations of the estimated error,then the method gets the estimated error to modify the estimates in the first step.The simulation results show that the Root Mean Square Error(RMSE)of this method is effectively reduced by selecting regularization parameters based on the CTLS model,and the positioning performance is more stable in the case of ill-conditioned coefficient matrix.3?A passive localization method(MWLS-FA)based on Modified Weighted Least Squares(MWLS)combined with Firefly Algorithm(FA)is proposed to solve the problem of low real-time performance in the case of 4 receivers.Firstly the proposed method uses the improved weighted least square method to get an initial estimate in the case of 4 receivers,after using the initial estimates to provide a dynamic search area for FA method,this method also make the adjustment and improvement in the aspect of the addition of constraints and the selection of parameters,the FA method is used to get the final estimate at last.The simulation experiment proves that the positioning accuracy of the MWLS-FA method proposed in this paper can reach the Cramer-Rao Lower Bound(CRLB)under the condition of 4 stations,and compared with the traditional search method,the MWLS-FA method has obvious improvement in anti-noise and real-time performance.