A linear programming approach to NLOS error mitigation in sensor networks
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In this paper, we propose an efficient non-line-of-sight (NLOS) error mitigation method for TOA measurement in indoor environments. In order to meet era of ubiquitous computing, there is a developing need for an accurate real-time locating system (RTLS). In the presence of a NLOS error, the location estimation performance is likely to be degraded. For effective location estimation, NLOS errors should be recognized and mitigated before measurements are used in conventional location estimation method such as non-linear least squares (NLS), linear least squares (LLS), weighted-linear least squares (WLS), and least median squares (LMS). For improve location estimation, we assumed that measured distances using weighing mitigation factor are exploited for location estimation. Through simulation results, theoretical analysis of the performance is demonstrated.