Arithmetical Analysis of WSN based Indoor Positioning Localization Systems with Kalman Filtering

(WSN) is used for determining the Indoor Positioning of objects and persons in recent years. WSN has been implemented in indoor positioning applications such as real-time tracking of humans/objects, patient monitoring in health care, navigation, warehouses for inventory monitoring, shopping malls, etc. But one of the problems while implementing WSN an Indoor positioning system is to ensure more coverage large number of sensors must be deployed which increases the installation cost. So, in this paper, MATLAB GUI named Sensor Network Localization Explorer to analyze the impact of node density on indoor aligning localization schemes. Later Kalman filter with the indoor positioning system to increase the reliability and reduce localization error of the system is introduced with a lesser number of nodes.