Accurate And Direct GNSS/PDR Integration For Pedestrian Smartphone Navigation In Multipath Environment

With the proceedings of well-described literature concerning the work history of multipath mitigation in the global navigation satellite systems(GNSS),multipath remains one of the major dominant factors in a challenging environment.In recent years,GNSS has been extensively used to mitigate the multipath effect and improve smartphone navigation.There are certain unperturbed harsh circumstances where GNSS signal cannot reach,thus making smartphone navigation preposterous.With pursuing intellection,the central objective of this thesis work is to find an accurate solution for pedestrian smartphone navigation in a multipath environment.Experiments are done with a micro-electro-mechanical system(MEMS)sensors mounted on a smartphone and no extra hardware is needed.The latest Android smartphone is used to log data files of GNSS and MEMS sensors.This schema is classified in the real synopsis and rectangle route length with three perpendicular turns have been selected for a pedestrian walk.The data is preprocessed using a low pass filter to remove unwanted noise and smooth the signal.The description of the accumulative error produced by the heading and step size estimation has been reduced by implementing the index mean cumulative heading error(MCHE)and cumulative step length error(CSLE)respectively.In the end,the optimal extended Kalman filter(EKF)algorithm is implemented to fuse the data of GNSS and PDR for final results.In this thesis,a novel technique has proposed to accurately give pedestrian smartphone navigation solution.The fusion results show that the prospective method explores the liability to use smartphone navigation in any case when the GNSS or PDR information is unavailable.The fusion results are also compared with other available navigation solutions.Substantial simulations are implemented and corroborate that the schemed method is sturdier than the prevailing algorithms and aim of higher accuracy is achieved with an ultra-low-cost solution.