Title :
Compressive sensing applied to fingerprint-based localisation
Author :
Qiao Cheng ; Munoz, Max ; Alomainy, Akram ; Yang Hao
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Queen Mary, Univ. of London, London, UK
Abstract :
Accurate localisation has always been a hot topic for indoor environment. Recently, compressive sensing has been applied to fingerprinting based localisation and achieved good performance. This paper provides an overview of the state-of-the-art compressive sensing based indoor localisation techniques and an introduction to potential solutions to challenges faced by current systems. The main focus is on the drawbacks of the existing techniques and possible future development.
Keywords :
RSSI; biomedical communication; compressed sensing; fingerprint identification; health care; indoor radio; wireless LAN; wireless sensor networks; compressive sensing; fingerprinting based localisation; indoor localisation techniques; Accuracy; Compressed sensing; Fingerprint recognition; Sensors; Sparse matrices; Vectors; Wireless sensor networks; Compressive sensing; RSSI; fingerprinting; indoor localisation; sparse approximation;
Conference_Titel :
RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-Bio), 2014 IEEE MTT-S International Microwave Workshop Series on
Conference_Location :
London
Print_ISBN :
978-1-4799-5445-2
DOI :
10.1109/IMWS-BIO.2014.7032449
