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Enhanced Least-Squares Positioning Algorithm for Indoor Positioning
Aug. 2013 (vol. 12 no. 8)
pp. 1640-1650
Ian Sharp, CSIRO, Marsfield
Kegen Yu, University of New South Wales, Sydney
This paper presents an enhanced least-squares positioning algorithm for locating and tracking within indoor environments where multipath and nonline-of-sight propagation conditions predominate. The ranging errors are modeled as a zero-mean random component plus a bias component that is assumed to be a linear function of the range. Through minimizing the mean-square error of the position estimation, an expression for the optimal estimate of the bias parameter is obtained. Both range and pseudo-range-based positioning are considered. Simulations and experimentation are conducted which show that a significant accuracy gain can be achieved for range-based positioning using the enhanced least-squares algorithm. It is also observed that the pseudo-range-based least-squares algorithm is little affected by the choice of the bias parameter. The results demonstrate that the experimental 5.8-GHz ISM band positioning system can achieve positional accuracy of around half a meter when using the proposed algorithm.
Index Terms:
Position measurement,Base stations,Measurement uncertainty,Mobile communication,Algorithm design and analysis,Standards,Accuracy,experimental verification,Indoor positioning,positional accuracy analysis,enhanced least-squares algorithm,multipath and nonline-of-sight propagation,range and pseudo-range,optimal bias parameter
Citation:
Ian Sharp, Kegen Yu, "Enhanced Least-Squares Positioning Algorithm for Indoor Positioning," IEEE Transactions on Mobile Computing, vol. 12, no. 8, pp. 1640-1650, Aug. 2013, doi:10.1109/TMC.2012.124
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