Research On Indoor Positioning Method Based On The Android Platform

With the constant progress of science and technology,people's demand for precision positioning and navigation services is also growing.It has not only confined to the outdoor navigation and positioning,but also to the precise indoor positioning.Due to the complexity and particularity of the indoor environment,the Global Positioning System(GPS)used for outdoor positioning can't meet the demand of the indoor positioning.Thus,the indoor positioning system that can provide faster,higher accuracy and more convenient positioning has become a hotspot of the researchers than ever.Based on the above background environment,the indoor positioning method based on Pedestrian Dead Reckoning(PDR)is studied in paper.In order to get more accurate location information,an estimation method of step length is presented in this paper.This value can be dynamically adjusted in the test process,and it is more consistent with the actual step length of the tester.Therefore,the accuracy of positioning can be improved.Through the study of a variety of wireless location methods,the indoor location method based on the Received Signal Strength(RSS)fingerprint is selected in this paper.Through the analysis of the two main stages of this method,we can find that the K-mean clustering method is used to establish offline fingerprint database.The computation of RSS fingerprint positioning can be reduced,and the speed of positioning can be improved.For the online matching stage,the Weighted K-Nearest Neighbor(WKNN)algorithm can be used to improve the accuracy of positioning.By the analysis and study of PDR and RSS fingerprint positioning method,it can be found that the PDR positioning has high stability in short time and short distance.But this method is not suitable for long time and long distance because it has accumulated errors.The RSS fingerprint positioning does not have accumulated errors and the signal has wide range,but the reason why the location is not continuous is that the signal is not stable and space symmetry.Thus there are jumping points.Based on the advantages and disadvantages of the above two methods of positioning analysis,the fusion positioning algorithm of PDR and RSS fingerprint positioning is proposed in this paper.In this algorithm,an effective judgment method based on the comparison of wireless signal intensity is proposed,which can solve the problem of discontinuity of location results in RSS fingerprint localization.This problem is due to the instability of the wireless signal.In addition,the fusion algorithm is proposed in this paper corrects the current position by introducing the map matching method,Thus,it can reduce the error of positioning.This paper also proposes a fusion method based on the adaptive parameter.The parameter can be dynamically adjusted according to the real-time accuracy of PDR and RSS fingerprint positioning in the positioning process.The high precision positioning method occupies a larger weight in the process of fusion.In this paper,an indoor positioning system is designed and implemented on the Android platform.The experimental results show that the fusion indoor positioning algorithm based on PDR and RSS fingerprints that is proposed in this paper can make the advantages of the two positioning methods complementary.The positioning system that is developed in this paper is low cost and easy to carry,so that it can be widely promoted and applied.