Localizing a Wireless Node in a Multi-Agent System using Kalman Filtering

Kalman Filtering has been successfully applied to various state estimation problems in mobile robotics. This paper presents the application of Kalman Filtering to a scenario where the measurements do not come as a time series. There is also no readily available estimation matrix for the system. The advantages and limitations of using Kalman Filtering in such a scenario are discussed. The work describes a strategy for position estimation of a wireless node (e.g. a mobile robot or any other portable device) while using only the line-of-sight distance estimates from the node to other nodes in its environment .