Abstract
A novel non-line-of-sight (NLOS) error identification and range measurement reconstruction algorithm is proposed. First, a NLOS error identification technique is exploited to decide whether there is a NLOS path from the base station (BS) to the mobile station (MS); Second, a biased Kalman filter (KF) is used to mitigate NLOS error in the raw measurements; and then, two measuring points which have maximum residual (so-called the upper dead point and the lower dead point) are investigated to suppress the NLOS error as well as measurement noise. Under the assumption that the NLOS range measurements have been identified, we propose an orthogonal polynomial to smooth the range measurements estimated by KF and a range measurement reconstruction model to suppress NLOS error. Simulations verify its effectiveness to true range reconstruction as well as location tracking in NLOS environment.
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© 2009 Springer-Verlag Berlin Heidelberg
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Chen, S., Liu, J., Xue, L. (2009). A Robust Non-Line-Of-Sight Error Mitigation Method in Mobile Position Location. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_18
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DOI: https://doi.org/10.1007/978-3-642-01513-7_18
Publisher Name: Springer, Berlin, Heidelberg
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