Research On Single Station Passive Target Location

Electronic warfare is a vital part of modern warfare.Passive target positioning systems have become one of the important components of electronic warfare due to their advantages such as strong concealment,resistance to electromagnetic interference,and high survivability.And also become important means to achieve automatic positioning and tracking.The passive target positioning refers to a positioning method that determines the position information of the target by relying on the received target to emit or backscatter the electromagnetic wave while the system does not emit electromagnetic waves.According to the number of base stations,passive target positioning is divided into single-site passive target positioning and multi-site passive target positioning.At present,the multi-passive passive target positioning system has achieved practical application,but the single-passive passive target positioning system still remains to be developed.Therefore,in this paper,the following research is done to address the problem of single-passive target positioning.First,the classic multi-station TDOA passive target positioning algorithms:WLS algorithm,Taylor algorithm and Chan algorithm are applied to single-station passive target positioning system,and simulation experiments are performed.Simulation experiments prove that the Chan algorithm does not have an initial value problem,so the positioning performance is better than the Taylor algorithm under high noise conditions.However because Chan algorithm ignores more than second-order noise,as the noise increases,the RMSE of the estimated value gradually deviates from CRLB.Second,based on the typical single-site passive target positioning algorithm of TDOA and FDOA,a combination algorithm combining TSWLS and offset compensation is proposed.This combination algorithm combines the TSWLS algorithm and the MLE-based deviation compensation algorithm.While retaining the closed-form solution of the TSWLS algorithm without the initial value and convergence problems,the deviation compensation method is used to improve the poor positioning performance of the TSWLS algorithm in high noise environments,and positioning accuracy.Third,simulation experiments are performed with the combination method of TSWLS and deviation compensation algorithm.Simulation experiments show that the combined algorithm is superior to the classical positioning algorithm in positioning performance and has better robustness to high noise.Furthermore,the positioning performance of the combined algorithm under different base station ranges and different target distances is simulated and analyzed.Experiments show that the positioning accuracy of the combined algorithm is higher than the TSWLS algorithm.And the closer the distance between the target point and the receiver,the higher the positioning accuracy of the algorithm,the wider the range of base stations,and the higher the positioning accuracy combined with the algorithm.According to the above simulation analysis,it is shown that the combined algorithm of TSWLS and bias compensation proposed in this paper is superior to the typical single-site passive target positioning algorithm of TDOA and FDOA,which can achieve fast and high-precision positioning of moving targets,and has certain engineering practicability.