Study And Implementation Of Ultra-wideband Indoor Positioning Algorithm Based On Beetle Antennae Search Particle Filtering Algorithm

In recent years,Ultra Wide Band(UWB)technology has been widely used in indoor positioning.There are mixed environments of line of sight(LOS)and non-line of sight(NLOS)in UWB indoor positioning,which puts forward higher requirements for the continuity and accuracy of positioning algorithms.Particle filtering is often used to solve this problem,but it has the defects of large amount of calculation and particle degradation.In this paper,we try to deal with this challenge by proposing a hybrid filtering solution,which integrates Particle Filter and Beetle Antennae Search algorithm,and design experiments in the real scene to verify the validity and engineering feasibility of the algorithm.The research content mainly includes three parts:(1)Based on the maximum likelihood TDOA positioning algorithm,a basic two-dimensional indoor positioning model is established,and the traditional particle filter algorithm is used to filter and correct the initially obtained positioning results to reduce the positioning error in mixed scenes;(2)Integrating the Beetle Antennae Search algorithm,the particles are distributed in the high-likelihood area through continuous iteration,which solves the particle degradation problem of the traditional particle filter algorithm,reduces the number of particles,and reduces the amount of calculation;(3)The UWB indoor positioning software and hardware platform is designed and constructed,and the algorithm is verified in actual scenarios.The experimental results show that in the LOS environments,the average positioning error of the Particle Filter Algorithm is about 15 cm,which is slightly better than the 17 cm of the traditional particle filter algorithm with the same number of particles.While in the mixed environments of LOS and NLOS,the average positioning error is about 28 cm,which is better than 43 cm of the traditional particle filter algorithm with the same number of particles;under the condition of the same positioning error,the number of particles required by the Beetle Antennae particle filter algorithm is 85% lower than that of the traditional particle filter,and the calculation amount is reduced by nearly 62%.