A linear programming approach to NLOS error mitigation in sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Robust statistical methods for securing wireless localization in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Least squares algorithms for time-of-arrival-based mobile location
IEEE Transactions on Signal Processing
Ranging in a dense multipath environment using an UWB radio link
IEEE Journal on Selected Areas in Communications
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In this paper, a new method is proposed for low complexity localization based on measured/estimated ranges. First, it is proved that the method provides a better estimator than the well known non-iterative direct methods documented in literature, i.e. the Spherical Interpolation and the Linear Least Squares method. It does so by exploiting two similar full constrained models. The proposed estimator is better, in the sense that it corresponds to an equal or smaller value of the original least-squares objective function. Second, the method goes without iterations, and therefore requires considerably less computation power than the iterative techniques such as the Gauss-Newton method. Validation is performed based on actual Ultra-WideBand (UWB) radio measurements conducted in typical office environments, with signal bandwidths varying from 1 to 7.5 GHz. Results show that the position estimates obtained with the proposed non-iterative method have lower root mean squared errors than any other tested well-known direct methods.