Abstract:

With the rapid development of information technology, indoor localization technology has become one of the most important research hotspots in location based service (LBS). Hybrid algorithms combining the received signal strength (RSS) location fingerprinting and pedestrian dead reckoning (PDR) can effectively improve the localization accuracy, but existing algorithms can hardly achieve higher localization accuracy and smaller calculation simultaneously. The common Kalman filter algorithm has limit localization accuracy while a large amount of calculation is required by the particle filter algorithm. We propose a hybrid localization algorithm based on multifingerprint union matching, which fuses the inertial sensor and the RSS fingerprint information effectively. Under the premise of low calculation amount, it can achieve higher precision of localization. Experimental results show that, 80% of the errors remain within 1m and the average accuracy reaches as high as 0.77m.

Key words: indoor localization, received signal strength (RSS), location fingerprinting, pedestrian dead reckoning (PDR), inertial measurement