Research On Optimal Location Of Passive Time Difference Based On Swarm Intelligence Algorithm

In modern war,how to get the enemy’s position quickly and accurately is the key guarantee to winning the war.Passive time difference location technology has been widely studied because of its high positioning accuracy and strong concealment.The layout of the observation station is one of the main factors affecting its positioning accuracy.With the development of swarm intelligence algorithms,scholars generally use swarm intelligence algorithms to improve the layout of observation stations,but there are still some shortcomings.First,the traditional swarm intelligence algorithm has the disadvantage of slow convergence speed,which makes it impossible to achieve the optimal station layout quickly.Second,most of the current studies are aimed at the scene of unknown radiation source location,but there is a lack of research on location optimization of known radiation source trajectory.To solve the above problems,the research contents of this thesis are as follows:Firstly,this thesis introduces the traditional localization algorithm,and determines the localization algorithm used in this thesis on the basis of analyzing the characteristics of the algorithm.Then,the GDOP expression is derived in detail,and the main factors affecting the positioning accuracy of passive time difference are obtained.Then,taking the fourstation time difference positioning as an example,the influence of each factor on the positioning error distribution is simulated and the suggestions for regular positioning are given.Finally,aiming at the problem of blind location in simulation,this thesis studies the cause of no solution and fuzzy location,analyzes the influence factors of no solution and fuzzy location by simulation,and gives the solution measures of no solution and fuzzy location.Second,the passive time difference method is studied when the location of the radiation source is unknown.In this thesis,the optimal station problem is transformed into the problem of solving the optimal solution,then the mathematical model of the optimal solution is established,and the independent variables,constraints,and objective functions of the model are given.Then,aiming at the defects of the traditional swarm intelligence algorithm,this thesis improves the salps group algorithm.By changing the number of leaders of the algorithm,the convergence speed of the algorithm is enhanced and the positioning accuracy is improved.Then,four algorithms are used to solve the problem under the unified simulation conditions,and the advantages and disadvantages of the four algorithms on the passive time difference problem are compared.Thirdly,the optimization problem of station distribution based on the known approximate flight path of the radiation source and the existing fixed station is studied.In this thesis,a single UAV is proposed to assist the existing fixed observation station to optimize the station layout,and then the optimization problem is transformed into an optimal solution problem,and the problem is modeled mathematically.Then the improved salps group algorithm,the unimproved algorithm,and the traditional intelligent algorithm are used to solve the simulation problem,and finally,the UAV-assisted station scheme is given.