Research On Multipoint Location Method Based On Improved Sparrow Algorithm

With the continuous progress of society,travel and transportation methods have become more diverse,making the aviation industry develop rapidly,so air traffic safety issues are becoming increasingly serious.At present,the traditional surveillance infrastructure(radar)of airports has been developed for many years and has reached a certain scale.As a new surveillance technology,multi point positioning technology(MLAT)will become a necessary technology for future civil aviation surveillance systems due to its advantages of high positioning accuracy,low cost,and wide coverage.In the field of multi-point positioning technology target tracking,particle filter(PF)algorithms are commonly used to track their targets.The traditional particle filter itself is not perfect,resulting in particle depletion and reduced estimation accuracy,leading to unstable filtering accuracy and inaccurate positioning.To address these issues,a Sparrow Search Algorithm Particle Filter(SSA-PF)based particle filter for target trajectory tracking is proposed.The sparrow algorithm is used to find the optimal value,and the optimized particles move towards the high likelihood region,improving the weight of the particles,improving the overall quality of the particles,and alleviating the particle dilution problem.The final simulation experiment shows that the filtering performance of SSA-PF algorithm is improved,and the performance of trajectory tracking and positioning is better.It can effectively solve the problem of target tracking error,and has strong feasibility.Chan algorithm and Taylor algorithm are introduced respectively for the positioning algorithm of multi-point positioning technology.Based on the traditional Chan algorithm,an improved Sparrow Search Algorithm-Chan(ISSA-Chan)method based on the improved Sparrow algorithm is proposed.The first step is to improve the Sparrow algorithm.The improved Sparrow algorithm is used to search for the optimal solution in space to reduce unnecessary global search.The optimal solution is substituted as an initial guess value into the Chan algorithm,and the initial solution estimation matrix B is obtained.Then,two weighted least squares(WLS)solutions are performed,which can effectively improve positioning accuracy and solve the problem of poor positioning accuracy,with good stability.Finally,from different experimental perspectives,simulation experiments are conducted to compare the ISSA Chan algorithm with Taylor algorithm,Chan algorithm,and PSO-Chan algorithm,and it is concluded that the ISSA Chan algorithm has the best positioning effect.In the deployment application of multipoint positioning technology,select six different locations on the campus to place base stations,conduct multipoint positioning system experiments,receive and decode data,and obtain a large amount of experimental data.Use ISSA Chan algorithm to optimize the deployment of base stations.Then,the current main evaluation indicators are introduced,and four conventional geometric layout GDOP distribution simulations are conducted.Next,we discuss the distribution of GDOP simulations for different flight altitudes of aircraft with the same number of base stations.Finally,an experimental simulation is conducted on the ground base station deployment scheme based on ISSA-Chan,and the effectiveness of the improvement is verified through comparison.