An adaptive environmental modeling localization method in Wireless Sensor Networks

Abstract

This paper presents a new localization algorithm in Wireless Sensor Networks. The RSSI (Received Signal Strength Indicator) is a localization method which provides an inexpensive and accurate solution for localization. However the time and location based fluctuations on the RSSI values and improper models cause a considerable localization error in the real applications. Most of the RSSI models suppose the radio range to be circular. In the proposed method the algorithm tries to find a relation between RSSI and distance for each anchor node in each direction adaptively and produce a noncircular model. The simulation results show that this method can reduce amount of the localization error considerably. Also unlike to the range free methods the proposed method can work properly in the low node densities.

Design and Realization of Precise Indoor Localization Mechanism for Wi-Fi Devices

“…Besides, Huang et al [19] develop a real-time RFID indoor positioning based on Kalman-filter to mitigate the drift of RSSI values. It is worth mentioning that Solhjoo and Tinati [20] try to find out the relationship between RSSI values and signal propagation distance among different direction of APs, and propose a non-circular signal propagation model. In [21], Guo et al develop an Exponential-Rayleigh (ER) model, which includes two parts, the large-scale part and the small-scale part, to mitigate the interferences caused by the multi-path when the signal is propagating.…”