Modified weighted centroid algorithm for indoor and outdoor positioning using wireless sensors network

Abstract

Positioning, either outdoor or indoor, has been one of the most attractive fields for researchers to study and they apply different approaches in order to allocate a moving object. Some positioning approaches use Received Signal Strength (RSSI) in order to determine the location such as Fingerprinting, and Weighted Centroid Localization (WCL). On the other hand, some approaches use signal travelling time such as Time of Arrival (TOA) and Time Difference of Arrival (TDOA). However, the accuracy is still low due to the effect of RSSI to moving objects. This paper shows how to allocate a blind node in a wireless sensor network (WSN) using the proposed WCL approach and shows how the enhancement of the algorithm made better accuracy with mean square error, MSE, of 64.5 cm for indoor positioning and 123.0cm for outdoor positioning. One of previous WCL approaches reached accuracy with an error of as low as 15.0 cm but in simulation, and others used different approaches with MSE of 80.0 cm and another as high as 2.6 m.