Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Indoor positioning based on statistical multipath channel modeling | Yen and Voltz EURASIP Journal on Wireless Communications and Networking 2011 2011 189 EURASIP Journal on . http content 20ii i i89 Wireless Communications and Networking a SpringerOpen Journal RESEARCH Open Access Indoor positioning based on statistical multipath channel modeling Chia-Pang Yen 1 and Peter J Voltz2 Abstract In order to estimate the location of an indoor mobile station MS estimated time-of-arrival TOA can be obtained at each of several access points APs . These TOA estimates can then be used to solve for the location of the MS. Alternatively it is possible to estimate the location of the MS directly by incorporating the received signals at all APs in a direct estimator of position. This article presents a deeper analysis of a previously proposed maximum likelihood ML -TOA estimator including a uniqueness property and the behavior in nonline-of-sight NLOS situations. Then a ML direct location estimation technique utilizing all received signals at the various APs is proposed based on the ML-TOA estimator. The Cramer-Rao lower bound CRLB is used as a performance reference for the ML direct location estimator. Keywords indoor positioning maximum likelihood ML time-of-arrival TOA direct location estimation 1 Introduction With the emergence of location-based applications and the need for next-generation location-aware wireless networks location finding is becoming an important problem. Indoor localization has recently started to attract more attention due to increasing demands from security commercial and medical services. For example next generation corporate wireless local area networks WLAN will utilize location-based techniques to improve security and privacy 1 . The requirement for high accuracy positioning in complex multipath channels and nonline-of-sight NLOS situations has made the task of indoor localization very challenging as compared to outdoor environments. Conventionally the positioning problem is solved via an .
