A big data-based RF localisation method for unmanned search and rescue. (2018) - Wang, Ju; Liu, Hongzhe; Bao, Hong; Montoya, Cesar Flores; Hinton, James
Autonomous mobile robots require efficient big-data methods to process a large amount of real-time sensory data to perform a task. We investigate a novel RF sensing-based method for target localisation where a large set of sensor data are mined to produce meaningful location information of a target device. The estimated location of the target is further used by the navigation algorithm to execute a movement plan. Using the networked RF beacon data, the proposed big data approach alleviates the problem of noisy RF measurements in location estimation. A particle filter algorithm is used to track the location of target node. The algorithm demonstrates a beyond-the-grid accuracy even only a coarse RF map is used.