An efficient clustering scheme for large and dense mobile ad hoc networks (MANETs)
Computer Communications
Non-Line-of-Sight Localization in Multipath Environments
IEEE Transactions on Mobile Computing
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Least squares algorithms for time-of-arrival-based mobile location
IEEE Transactions on Signal Processing
Hybrid TDOA/AOA mobile user location for wideband CDMA cellular systems
IEEE Transactions on Wireless Communications
Nonline-of-sight error mitigation in mobile location
IEEE Transactions on Wireless Communications
An overview of the challenges and progress in meeting the E-911 requirement for location service
IEEE Communications Magazine
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Current state of the art localization scheme is able to locate mobile device in multipath environment by using both Line of Sight (LOS) and Non Line of Sight (NLOS) Time-Of-Arrival (TOA) and Angle-Of-Arrival (AOA) information at both the mobile device and reference device side. Each set of measured TOA and AOA can be manipulated to form a line on which mobile device are most likely located, this line is called Line of Possible Mobile Device (LPMD). Intersection points of LPMD serve as the estimators of mobile device's position. LPMD concept only works with LOS and one-bounce-reflection measurement metrics and hence multiple-bounce reflection measurement metrics have to be eliminated. Current algorithm does not work well in environments whereby multiple-bounce reflection metrics are very dominant. In addition, weighting factors in current algorithm needs readjustments for different environments. This paper addresses novel methods to overcome those limitations. Furthermore, this paper also extends the problem to three-dimensional environment. Since LPMDs in 3D will in general not intersect with each others, proximate points instead of intersection points are used as estimators. A novel two-steps-weighting approach is proposed by first putting weighting factor on LPMDs and then on proximate points. Weighting factors are assigned to each LPMD path and the weighted-centroid is calculated. LPMDs that lie far from the centroid are eliminated because it is very likely that these are multiple-bounce reflection LPMDs. In addition, weighting factors are also assigned to proximate points and once again the weighted-centroid is calculated. Mobile position is approximated by taking mean of proximate points that lie within 3 standard deviations from the centroid. The proposed scheme outperforms previous bidirectional NLOS localization scheme by a significant margin.