Research On Bluetooth Positioning Algorithm And Intelligent Iron Shoe Terminal In Complex Environment Of Railway Station

In the daily operation of railway station,the hidden danger of vehicle slipping has become one of the most common and important accident hazards.The need for relevant means to reduce the huge losses caused by such hidden dangers in both necessary and urgent.Iron shoes are commonly used anti-skid devices on railways,in order to be able to grasp the working status of the anti-slip iron shoes in real time,and find out in time the poor adhesion between the non-slip iron shoes and the train wheels,the theft of iron shoes,slippage and other abnormal situations,it is necessary to develop an intelligent iron shoes anti-slip and anti-theft system for iron shoes,which can monitor the state,location information and slippage of iron shoes.This paper focuses on the indoor positioning algorithm based on iron shoes and the design of intelligent iron shoes terminal system,which provides new ideas for the design of intelligent iron shoes and indoor positioning methods.This paper firstly designs the indoor positioning algorithm based on the i Beacon.The defects of the current Bluetooth positioning algorithm based on RSSI（Received Signal Strength Indicator）are analyzed.At the same time,in view of the problems existing in the classical Bluetooth positioning method,a weight-optimized four-point positioning algorithm theory is proposed,and the particle swarm algorithm is used to solve this issue.The accuracy of the positioning algorithm is verified by simulation and experiments.In order to improve the positioning accuracy of the smart iron shoe terminal in motion,and make up for the lack of single Bluetooth positioning,an indoor positioning algorithm based on EKF（Extended Kalman Filter）fusion positioning is proposed,which combines Bluetooth positioning results and dead reckoning positioning.The feasibility and existing problems of the algorithm are analyzed by simulation.Through the single-factor simulation positioning test,the effects of different process noise and measurement noise on the positioning results were compared and analyzed.On the basis of analyzing the above results,an indoor fusion positioning algorithm of AEKF（Adaptive Extended Kalman Filter）with adaptive parameter noise is proposed and designed,and different algorithms are used for positioning simulation and positioning results comparison.It can be seen from the results that compared with the classical EKF fusion localization algorithm,the localization accuracy of AEKF fusion localization is higher.According to the functional requirements of the smart iron shoe terminal,this paper uses STM32L051 as the main control chip to design the hardware and software of the iron shoe terminal system.The specific functions of the system mainly include ranging,receiving Bluetooth signals,attitude detection,GPS positioning,and communication with the host computer.The hardware circuit mainly includes an Io T module,a charging module,a Bluetooth receiving module,a ranging module,and an Io T communication module.Combined with functional requirements,complete the schematic design of each module,and complete the PCB design.In the process of equipment software design,the main program is written based on the finite state machine,and the relevant sub-module programs are written,and the related functional modules are tested.Finally,based on the hardware platform,the related algorithms proposed in this paper are tested,and the reliability and stability of the proposed related algorithms are verified.