Signal Source Location Based On Optimized Particle Filter By Improved Firefly Algorithm

With the wide application of radio communication technology,signal source location technology has gradually became one of the key technologies in the field of radio monitoring technology.At the same time,the demand for location precision of signal source is increased.Based on the radio mobile monitoring vehicle,this thesis studies signal source location technology.Aiming at the problems such as the large errors of direction-finding data and the low precision of the location result,particle filter algorithm is used to estimate the location result.Besides,the improved firefly algorithms are introduced to improve the filtering effect and the location accuracy.Firstly,according to the location environment and the measurement parameters' characteristics of the mobile monitoring vehicle,the angle of arrival method is selected,and the signal source location models based on the angle of arrival is established which contains two dimensional model and three dimensional model.The implementing flow of the signal source location based on particle filter is given,and the simulation experiments are carried out.The experimental analysis shows that the particle filter algorithm has the problem of sample degradation,which has greatly influenced the location precision,and the particle filter algorithm needs to be further improved.Secondly,aiming at the low location precision of the signal source location based on particle filter algorithm,firefly algorithm is used to improve the particle distribution of the particle filter algorithm.Besides,according to the problems that firefly algorithm's iteration is slow and it is easy to trap into the local optimum,the global optimum value is introduced.The global attractiveness function is used to dynamically control global search ability and local search ability.The phenomenon of trapping into the local optimum is avoided.Signal source location based on adaptive firefly optimization particle filter algorithm is proposed.Through simulation experiments,it is proved that the introduction of adaptive firefly algorithm improves the precision of signal source location.Thirdly,aiming at the problem of increased computational complexity and poor real-time real-time performance of the location algorithm in the process of fusion between adaptive firefly and particle filter algorithms,the global optimal value is used to directly guide the movement of sample particles,and the attraction function is improved.Theimproved mechanism is introduced into the particle filter algorithm,and a particle filter localization algorithm based on the global optimization firefly algorithm is proposed to improve the convergence speed of the algorithm.The simulation results show that synthesis performance of the location algorithm is improved.Signal source location based on adaptive firefly optimization particle filter algorithm and firefly algorithm based on global optimization to optimize particle filter's signal source localization are verified by using the location experiments,and the effectiveness of the improved algorithms is further proved.Finally,in order to display the location process and location results intuitively,and make it convenient for users.The software development of the signal source location system is developed by using the GUI platform,and the human-computer interaction platform of the signal source location system is obtained.The platform includes signal source localization based on particle filter,signal source location based on adaptive firefly algorithm,and firefly algorithm based on global optimization to optimize particle filter's signal source localization.Through the location system,the users can import measured data and select a suitable location algorithm for signal source location,so as to achieve the purpose of obtaining the positioning results conveniently and quickly.