The Study Of Indoor Positioning Based On The Combination Of WiFi And PDR

At present,outdoor positioning and navigation technologies based on global positioning systems(GPS)are widely used worldwide and play a huge role in modern society.Compared with the outdoor environment,there are wall barriers,human body and electronic equipment signals and other interferences in the indoor environment,which make the signals received by the GPS very weak,even not perceptible.WiFi Positioning is highly dependent on the external environment,but the error of inertial navigation positioning technology increases over time.Therefore,this paper proposes the study of the indoor location method based on the combination of WiFi and PDR.WiFi signals are very common in indoor environment,so WiFi positioning system can use existing hardware resources to achieve absolute position estimation,and errors do not accumulate over time.The indoor positioning method based on inertial sensors— Pedestrian Dead Reckoning(PDR)does not depend on the external environment and can achieve autonomous positioning,but the error of this method accumulates over time.In this paper,after considering the advantages and disadvantages of the two positioning methods,a combined positioning method is adopted,and the WiFi positioning system and the PDR positioning system are integrated by using unscented Kalman filtering to improve the accuracy and robustness of indoor positioning.The contents of this paper are as follows:(1)The main reasons for the fluctuation of WiFi location estimation are the interference in indoor environment and the instability of the signal transmitted by the access point itself.This paper divided WiFi positioning into ranging positioning algorithms and non-ranging positioning algorithms according to the principle of WiFi positioning.In order to select a suitable positioning method,this paper chooses a positioning algorithm based on RSSI ranging after comprehensive analyzing and comparing the common algorithms in the two positioning algorithms.The main reason for the fluctuation of WiFi location estimation is the interference in the indoor environment and the instability of the signal transmitted by the access point itself.This paper proposes Multi-Directional Grouping Indoor WiFi Positioning,multi-angle ranging to avoid interference in a single direction,and multiple groups composed of multiple access points perform position estimation separately,eliminating the problem of position estimation of an access point itself Impact.(2)Aiming at the problem of high noise in the data collected by inertial sensor,the time series analysis method is established to preprocess the collected data,then the model is built,and the Kalman filter method is selected for optimization.In view of the interference of carrier magnetic field to magnetometer,low-pass filter is used to optimize the magnetometer data,and the magnetometer is calibrated and error compensated.(3)In order to solve the problems of erroneous step count and weak anti-interference ability of single way heading angle measurement,the dynamic time constraint and acceleration amplitude constraint is used to eliminate the false peak in the peak detection.In course angle calculation,the data collected by accelerometer,magnetometer and gyroscope are fused by extended Kalman filter to reduce course angle error.(4)The unstable WiFi Positioning and the increasing accumulated error of PDR positioning cannot meet the positioning requirements.Taking advantage of the advantages of combined positioning,the cumulative speed of accumulated error caused by PDR positioning can be slowed down by using unscented Kalman filter to combine WiFi Positioning System and PDR positioning system.