Ultra-wideband geo-regioning: a novel clustering and localization technique
EURASIP Journal on Advances in Signal Processing
Editorial: signal processing for location estimation and tracking in wireless environments
EURASIP Journal on Advances in Signal Processing
IEEE Transactions on Wireless Communications
Low complexity location fingerprinting with generalized UWB energy detection receivers
IEEE Transactions on Signal Processing
Towards context-awareness in ubiquitous computing
EUC'07 Proceedings of the 2007 international conference on Embedded and ubiquitous computing
Positioning in multibeam geostationary satellite networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
A dynamic system approach for radio location fingerprinting in wireless local area networks
IEEE Transactions on Communications
Indoor localization with channel impulse response based fingerprint and nonparametric regression
IEEE Transactions on Wireless Communications
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Advanced support vector machines for 802.11 indoor location
Signal Processing
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
From RSSI to CSI: Indoor localization via channel response
ACM Computing Surveys (CSUR)
| Hi-index | 0.01 |
The location of people, mobile terminals and equipment is highly desirable for operational enhancements in the mining industry. In an indoor environment such as a mine, the multipath caused by reflection, diffraction and diffusion on the rough sidewall surfaces, and the non-line of sight (NLOS) due to the blockage of the shortest direct path between transmitter and receiver are the main sources of range measurement errors. Unreliable measurements of location metrics such as received signal strengths (RSS), angles of arrival (AOA) and times of arrival (TOA) or time differences of arrival (TDOA), result in the deterioration of the positioning performance. Hence, alternatives to the traditional parametric geolocation techniques have to be considered. In this paper, we present a novel method for mobile station location using wideband channel measurement results applied to an artificial neural network (ANN). The proposed system, the wide band neural network-locate (WBNN-locate), learns off-line the location 'signatures' from the extracted location-dependent features of the measured channel impulse responses for line of sight (LOS) and non-line of sight (NLOS) situations. It then matches on-line the observation received from a mobile station against the learned set of 'signatures' to accurately locate its position. The location accuracy of the proposed system, applied in an underground mine, has been found to be 2 meters for 90% and 80% of trained and untrained data, respectively. Moreover, the proposed system may also be applicable to any other indoor situation and particularly in confined environments with characteristics similar to those of a mine (e.g. rough sidewalls surface).