Robustness of 3D indoor localization based on fingerprint technique in wireless sensor networks

The simple approaches of an indoor localization have been continuously developed and extensively published. In order to achieve a challenge of the effective indoor localization, the expected localization system should be a high efficiency such as high accuracy, simple, robustness and effective system. For the indoor localization, the researches have been supported by the advancement of the sensor node technology. One application of this technology is wireless sensor networks-based indoor localization. The simple approaches of 2-dimensional (2D) indoor localization have been widely proposed. Since a realistic system includes complicated terrain and different environment, 3-dimensional (3D) consideration is more suitable to be applied in the real life. This paper proposes an approach of 3D indoor localization based on ZigBee standard. Fingerprint technique-based received signal strength indicator (RSSI) is employed. Due to fluctuating signals in indoor environment, robustness of fingerprint technique will be proposed in order to solve the propagation mechanisms. The k-Nearest Neighbor using Euclidean distance is utilized as the pattern matching algorithm. For the case study, 8 reference nodes and 1 target node are stationary placed on a bookshelf in clean and human body's effect environments. The expected errors of estimated target locations should not be more than 36 cm (each level height). From the results, we can acquire an acceptable accuracy. It shows that our system can be applied in the real application. © 2013 IEEE.