Less-calibration Wi-Fi-based indoor positioning

Fingerprint-based indoor positioning technique is one of sustainable approaches to provide highly accurate information about mobile user´s location. However, it requires the constructing of a high-resolution radio map, which is time consuming and labor intensive. In this paper, a novel less-calibration Wi-Fi-based indoor positioning is proposed. The new technique takes advantage of regular mobile users´ movement inside the environment to build the radio map. During these movements mobile users can measure and record received signal strength (RSS) from available wireless access points. The radio map will be adapted to environment changes using the recent collected RSSs data. The proposed algorithm does not use extra hardware (e.g., accelerometer, magnetometer) to exploit the collected RSSs. Experimental results showed that the proposed technique can be used to build the radio map with surveying only one-third of the area of interest (about two-third of the effort is reduced). The achieved localization error and location precision are competitive with the current proposed solutions.