Indoor wireless sensor network localization using RSSI based weighting algorithm method

Now a day, appropriate and correct indoor positioning in wireless networks could provide interesting services and applications. However, there are more factors of the indoor environment caused to reduce the precise localization and also increase the error of distance. This paper presents a new method to evaluate the wireless sensor network (WSN) technology for the indoor localization. The weighting algorithms: the weight range localizer (WRL) and relative span exponential weight range localizer (RS-WRL) are using based on received signal strength indicator (RSSI) to estimate the position of target node. As the results, the cumulative distribution function (CDF) probability indicates the error of distance as properly, and this method can help to increase the precision of range based localization method in an application of indoor environment.