A big data-based RF localisation method for unmanned search and rescue. (2018)

• Record Type: Journal Article
• Authors: Wang, Ju; Liu, Hongzhe; Bao, Hong; Montoya, Cesar Flores; Hinton, James
• Is Part Of: International journal of big data intelligence. Volume 5:Number 1/2(2018)
• Page Start: 124
• Page End: 132
• Publication Date: 2018
• Subjects: RF mapping -- robot localisation -- navigation -- measurement mining; Big data -- Periodicals; 005.705
• Languages: English
• ISSNs: 2053-1389

Abstract

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.