TDOA Localization Based on Improved Harris Hawk Optimization Algorithm
摘要
To solve the nonlinear equation problem of indoor Time Difference of Arrival(TDOA) localization,this paper proposes a localization algorithm based on improved Harris Hawk Optimization(HHO),maintaining the optimization mechanism while enhancing the performance of HHO.The proposed algorithm improves the fitness function based on maximum likelihood estimation to obtain better fitness value in the optimization process,which increases the optimization accuracy.Meanwhile,the initial solution is introduced into the initial population position,which reduces unnecessary global search and improves the convergence speed of the algorithm without affecting the population diversity.Simulation results show that,compared with DHHO/M,EWOA,IALOT and CSSA algorithms,the proposed algorithm has higher localization accuracy and convergence speed.