Ultra Wideband Indoor Positioning Algorithm And System Implementation Based On Improved Butterfly Algorithm

In recent years,Ultra Wide Band(UWB)has been widely used in indoor positioning.Due to the complex indoor environment,it is challenging to maintain the positioning accuracy and positioning continuity throughout the positioning process as the positioning target is moving due to the presence of Line of sight(LOS)and Non line of sight(NLOS)scenarios.This paper investigates the UWB indoor positioning algorithm and the error smoothing algorithm after positioning in LOS/NLOS hybrid scenes,specifically by introducing the butterfly optimization algorithm into the UWB positioning and filtering in LOS/NLOS hybrid scenes.On the one hand,it solves the root mirroring problem in the conventional Spherical Intersection(SX)algorithm based on Time Differences of Arrival(TDOA)in a specific scene,and on the other hand,it smoothly filters the localization results to reduce the localization errors in the NLOS environment and ensure the localization continuity.The main research elements of this paper are as follows:(1)This paper proposes a butterfly fusion SX localization algorithm to solve the problem of selecting the root mirror of the SX localization algorithm in the specific scenario of two-dimensional UWB indoor localization of three base stations.Firstly,the butterfly algorithm uses the previous UWB positioning results to predict the current tag location;by calculating the distance between the predicted location coordinates and the two location coordinates solved in the SX positioning algorithm,the one with the smaller distance is selected as the current positioning result.This effectively solves the root selection mirroring problem in the traditional SX algorithm,where the positioning result is selected based on the condition of positive root only;(2)In order to address the problems of particle degradation and large computation in UWB indoor localization filtering,an improved butterfly particle filtering algorithm based on variational operators is proposed.The algorithm mainly solves the problems that the butterfly algorithm is easy to fall into local optimum and low speed of later finding by introducing variational operators,and fuses the improved butterfly algorithm with particle filtering for UWB indoor localization result filtering in LOS/NLOS hybrid scenarios.The simulation results show that the introduction of the butterfly particle filtering algorithm to filter and correct the UWB localisation results reduces the localisation errors and improves the localisation continuity in the hybrid LOS/NLOS scenario;(3)A UWB indoor positioning software and hardware platform system is developed,and two indoor positioning scenarios are designed to verify the effectiveness and feasibility of the butterfly particle filtering algorithm.The experimental results show that: in both scenarios,the algorithm performance of the improved butterfly particle filtering algorithm is better than that of the traditional particle filtering algorithm,reducing the complexity of the algorithm and the localization error;in the LOS scenario,the average localization error of the improved butterfly particle filtering algorithm is about 17 cm,which is lower than the 20 cm of the traditional particle filtering algorithm;in the LOS/NLOS hybrid scenario,the average localization error of the improved butterfly particle filtering algorithm is about 28 cm,which is much lower than that of the equivalent particle filtering algorithm.In the LOS/NLOS hybrid scene,the average localization error of the improved butterfly particle filtering algorithm is about 28 cm,which is much lower than the 43 cm of the conventional particle filtering algorithm with the same number of particles;with the same localization error,the number of particles required by the improved butterfly particle filtering algorithm is 75% lower than that of the conventional particle filtering algorithm.