Research On Key Technologies Of Multi-Station Passive Location Based On Angle Of Arrival

With the increasing complexity of the electromagnetic environment,the importance of accurate positioning of target radiation sources is increasingly significant.Passive location technology has gradually become a hot research topic in academia due to its advantages of good concealment and strong anti-interference ability.Among them,the azimuth information obtained by the passive location method based on angle of arrival is relatively reliable,and the multi-station location can utilize more measurement information to reduce localization error.Therefore,the multi-station location technology based on angle of arrival is widely used in wireless sensor networks,unmanned aerial vehicle communications and other fields.In the process of multistation location based on angle of arrival,the optimal selection of observation stations and the research and improvement of localization algorithms are important measures to improve target localization accuracy.This article mainly focuses on these two aspects.Firstly,regarding the problem of station location selection,a method for optimizing the combination of localization stations based on discrete optimization is proposed.After completing the construction of the station optimization model and setting of objective function and constraint conditions,the method refers to the idea of traditional discrete particle swarm optimization algorithm,adopts an indirect discretization of particle position parameters to randomly combine multiple stations in the localization system.Through compares the objective function values under different observation station combination,so as to obtain the observation station combination form with higher localization accuracy,achieving optimal station selection.Secondly,in the aspect of target localization algorithm research and improvement,an improved algorithm of multi-station direction finding location based on particle swarm optimization is proposed.The improved algorithm improves the particle searching ability by integrating the least squares localization algorithm,improving the particle swarm parameters,and introducing Metropolis criterion,in order to obtain the global optimal localization solution more quickly.The algorithm does not require iterative initial values and is simple to implement,and the localization error tends to the Cramer Rao Lower Bound.Especially,when the angle measurement error is large,it has significant advantages in improving the localization performance compared with other multi-station direction finding localization algorithms.Finally,based on the above research,a passive multi-station direction finding localization software platform is built using VS2010 tool.The platform realizes the functions of optimal station selection,target location estimation,localization error calculation,and localization data retention and display,and achieves the purpose of real-time positioning of targets.