A Novel High Accuracy Indoor Positioning System Based on Wireless Lans

Abstract

Abstract-A novel indoor positioning system based on received signal strength (RSS) in wireless networks with high accuracy is presented in this paper. The three improvement mechanisms, called signal strength filter, user location filter and path tracking assistance, are employed to improve the positioning accuracy of the system. The comprehensive performance of the proposed system is analyzed in detail and compared with the Radar system. Experimental results demonstrate that the proposed system in this paper can improve 80% accuracy in 3 meters of Radar system to 93% in typical office building testbed. Therefore, the indoor positioning system presented in this paper has the advantages of high accuracy, low cost and easy expansibility, and it can be used to locate people and assets in the fields of logistics, healthcare, and manufacturing.

Indoor Location Estimation Utilizing Wi-Fi Signals

“…The lowest values are 6, 8 and 9 at RL 12, 17, and 31 with matrix of (1,12), (1,17) and (2,12). [15], 2.5m average error from actual location is still accepted and valid. It also states that there is no need to take too nearest RL between neighbors.…”

Indoor Localisation Based on GSM Signals: Multistorey Building Study

“…Regrettably, they are not suitable for indoor environments-because of significant loss in the GPS signal strength. Therefore, many different methods for positioning in indoor situations have been proposed: [9,[11][12][13][14][15][16][17]. These employ different technologies, for example, WiFi, Bluetooth, infrared, and various algorithms for position calculation, using proximity, distance or angle estimation, and complex analysis of the scene.…”

The proposed System for Indoor Location Tracking

“…To reduce the high sensitivity of the measured values to the surrounding environment, the I3BM employs mechanisms as signal filtering and room adjacency utilization. As there are many factors influencing the signal readings, it is irrational to base the positioning decision upon a single measurement, but rather upon the outcome of filtering a group of signal values [4] [8].…”

“…Assuming that noises tend mainly to reduce the signal strength, a MAX filter has demonstrated good performance, where the selected RSSI value is the maximum received value for a sequence of packets communicated between the mobile and each beacon node over a pre-specified period of time [8]. Room adjacency utilization also improves accuracy of location estimation where people move according to feasible paths.…”