Design And Development Of Indoor Positioning And Navigation System Based On Mobile Terminal

With the increase of wireless network technology and mobile devices,people’s demand for acquiring their own location anytime and anywhere is increasing,especially for indoor location information.At the same time,because of the advantages of wireless network,such as fast speed,low cost,simple deployment,and various sensors built in mobile devices,the rapid development of indoor navigation technology is also promoted.Based on the existing indoor positioning and navigation of WiFi and mobile sensors,this paper studies from four aspects: WiFi signal filtering processing,improved algorithm based on cosine distance,pedestrian track calculation and WiFi fusion algorithm,and Android program design and implementation,and makes a detailed comparative analysis of the relevant methods,and puts forward corresponding improvement methods for the existing problems of the original methods.Finally,an indoor positioning and navigation app based on Android system is designed and implemented,which verifies the feasibility of the method.The main work is as follows:(1)In view of the phenomenon of acquisition information jump in WiFi indoor positioning,Kalman filter is used to smooth and reduce noise.The feasibility of several received signal strength(RSSI)algorithms is compared and analyzed,and the advantages of Kalman filter for RSSI value smoothing are verified,so as to build a more reliable WiFi signal fingerprint database in the test area.(2)The fingerprint matching and location algorithms in the online location stage are compared.For multi-dimensional vector fingerprint data,we compare the advantages and disadvantages of similar fingerprint matching algorithms such as Euclidean distance and cosine distance.Cosine distance is used to match fingerprint and improve the positioning accuracy.(3)In order to solve the problem of pedestrian track passing through obstacles and reduce the inherent cumulative error of pedestrian track estimation method,particle filter and indicator setting are added to PDR method.When users pass these indicators,they are compared with each other,so as to correct the user position estimated by particle filter.The weight of each particle is modified by using the obstacle information in the map,and the user’s position is obtained by weighted sum of particle swarm’s position.If all particles die,the user’s position is obtained by WiFi Positioning to reactivate the particle swarm.The experimental results show that the algorithm can solve the problem of cumulative error and pedestrian path crossing obstacles to a certain extent.(4)On the basis of Android system and Apache server based on xampp software deployment,an indoor positioning and navigation system based on WiFi and sensor fusion is designed and implemented,which verifies the feasibility of the method.