Research On Target Location Based On Base Station Passive Optimization Method

At present,electromagnetic wave information has a trend of becoming more and more complex,and the processing requirements for target positioning information are increasing,Passive base station positioning technology has the advantages of low equipment requirements,simple information required,and good stability,so it has received extensive attention and research.Passive positioning technology mainly includes time difference positioning technology(Time Difference of Arrival,TDOA),frequency difference positioning technology(Frequency Difference of Arrival,FDOA),direction finding positioning technology(Angle of Arrival),etc.Among them,TDOA positioning technology is more common.Because of its better positioning accuracy and stability,it has been widely used.Based on the time difference positioning technology,this article improves some of its own problems and further improves its performance;for maneuvering targets,it uses angle information and frequency difference information combined,and introduces an improved particle filter algorithm to achieve the Target tracking.The research content of this article is as follows:(1)This article first explains the basic positioning principles of passive base stations,and proposes the information and processing methods needed for positioning technologies such as time difference and frequency difference.On this basis,it analyzes its current positioning information processing method,summarizes and summarizes its advantages and disadvantages,and proposes to introduce an Improved Whale optimization algorithm(IWOA)to adjust the current method according to the nonlinear characteristics of its positioning problem.The inferiority of the system,thereby further improving the accuracy of positioning.For maneuvering target sources,by combining angle information and frequency difference information as the background,the maneuvering target is tracked,and on this basis,the shortcomings of the current filtering methods are analyzed,and the filtering method of this article—particle filtering is proposed according to the characteristics of joint information.,And on this basis,the intelligent algorithm is further introduced to adjust the filtering process to make the algorithm more suitable for positioning and tracking problems.(2)This article analyzes and establishes the mathematical model of multi-station time difference positioning for the time difference positioning technology,conducts mathematical analysis on the physical model,uses the maximum likelihood estimation method to construct the model formula,and further improves the model for the different impact of different base stations on the target.,And by entering and adjusting the intelligent algorithm,it can better solve the nonlinear problem of the time difference model proposed in this paper.For maneuvering targets,combining frequency difference information on the basis of angle information,constructing a mathematical model of joint angular phase-frequency difference positioning based on a single base station,and combining angle information and frequency difference information as a background to further reflect the state of the maneuvering target Information,the problem of tracking the target is transformed into the problem of estimating the state of the target,and from this,the improved particle filter processing method in this paper is proposed,and the particle filter method is improved by introducing a Salp swarm algorithm(SSA),Use the improved algorithm to statistically estimate the target status information,which can realize the real-time passive position judgment of the maneuvering target using a single station.(3)Carry out logic derivation and simulation experiment verification.Compared with other algorithms,the multi-station improved whale algorithm’s time difference passive location algorithm has improved accuracy and good stability;The improved Salp swarm algorithm proposed in this paper for maneuvering targets can effectively deal with the problem of tracking the source of maneuvering targets.Compared with other algorithms,it has better comprehensive positioning performance and better robustness from the perspective of accuracy and time.