Research And Implementation Of Unconstrained Pedestrian Navigation Algorithm Based On Smartphone

In recent years,thanks to the growing development of the national economy,the urbanization process has continued to accelerate,and urban construction planning is changing with each passing day.The demand for Location Based Services(LBS)from individuals and markets are also growing by the emergence and improvement of emerging technologies such as Smart Cities,Intelligent Transportation,and Internet of Things.With the continuous development of MEMS technology,the calculation capability of smartphones is becoming more and more powerful,and the types of internal sensors are also becoming more and more abundant.Therefore,using smartphones as a medium to achieve pedestrian navigation has become an important research content in the field of navigation research.In this paper,the unconstrained pedestrian navigation and positioning method based on smartphone and pedestrian navigation will be studied.Firstly,the paper analyzes the domestic and international research status of indoor positioning technology,smartphone-based positioning technology and machine learning-based positioning technology.Combined with the advantages and disadvantages and technical difficulties of pedestrian navigation technology based on smartphones,an unconstrained pedestrian navigation positioning method based on smartphones has been proposed in this paper.Aiming at the low precision of the sensor in smartphones and the change of posture when using smartphones,a new heading divergence suppression algorithm and attitude judgment algorithm are proposed,which realize the function of ensuring the navigation heading of smartphones unchanged when the posture of smartphones changed,and successfully improve the navigation accuracy and applicability of smartphones navigation.In order to solve the problem of the quick change of the zero offset and the error,the characteristics of the low cost inertial sensors,the paper first analyzes the sensor error in the smartphone,and then improves the existing Pedestrian Dead Reckoning(PDR)algorithm.Making the step judgment algorithm,the step size estimation and heading solution method can satisfy the pedestrian navigation research of handheld smartphones.Secondly,when pedestrian navigation is based on a handheld smartphone,there is no obtain zero-velocity status which makes Zero-Velocity Update(ZUPT)cannot be used in smartphone navigation.For this situation,after analyzing the pedestrian motion state and the data from the foot-mounted and handheld sensors,a Simulate Zero-Velocity Update(S-ZUPT)is proposed in this paper,which can effectively restrain the heading of smartphone pedestrian navigation and suppress the rapid divergence of errors.The meaning of unconstrained navigation is that accurate navigation positioning can still be achieved without fixing the smartphones.However,the existing inertial navigation methods for smartphones require a relatively fixed posture of smartphones to avoid the impact of smartphones' posture changes on navigation solution.To solve this problem,after studying the characteristics of smartphone sensor data output under various attitudes,a gesture judgment algorithm based on gravity spherical projection is proposed.Based on this algorithm,a smartphone heading correction algorithm is developed.In addition,the continuous development of machine learning has provided new ideas for navigation researchers.In this paper,the heading error of smartphones inertial navigation relative high precision differential GPS results is used as training set to predict the divergence law of mobile phone heading error,which further improves the positioning accuracy of smartphone navigation.Finally,based on the platform of MATLAB GUI,an experimental verification platform is developed to validate and analyze the unconstrained navigation and positioning method based on smartphone.The experimental results show that all the proposed algorithms can work independently,and effectively improve the accuracy of inertial positioning based on mobile phones,and improve the applicability of mobile navigation...