Abstract
Wireless location becomes difficult due to contamination of measured time-of-arrival (TOA) caused by non-line-of-sight. In this letter, TOA measurements seen at base stations are adjusted by scale factors, and a modified deterministic model is built. An effective numerical solution is proposed to resolve the scale factors and mobile position. A simulation comparison of four algorithms indicates that the proposed algorithm outperforms the other three algorithms.
Highlights
INTRODUCTIONMost time-of-arrival- (TOA-) based algorithms are derived from deterministic model
For outdoor wireless location, most time-of-arrival- (TOA-) based algorithms are derived from deterministic model
The mobile position is commonly modeled as the intersection of a set of circles defined by TOA ranges
Summary
Most time-of-arrival- (TOA-) based algorithms are derived from deterministic model. Very important contributions to the TOA-based location have been made to compute the mobile position using TOA measurements. The least-square (LS) criterion is often used to compute the estimate of mobile position, which is optimal if the residual follows Gaussian distribution. In the range scaling algorithm (RSA) in [5], the NLOS is mitigated using TOA adjustment by scaling NLOS-corrupted TOA measurements using factors that are estimated from a constrained nonlinear optimization process. Scale factors are employed to adjust TOA measurements seen at base stations, and a modified deterministic model is proposed. An effective solution is used to resolve the mobile position, which does not require prior knowledge of NLOS distribution or time-based history measurements
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