NLOS Measurement Identification for Mobile Positioning in Wireless Cellular Systems

An Integration Method for Wireless Location Using Built-in Sensors of Mobile Phones and TDOA Landmarks

“…In this part, the physical statistical properties of a user's movement at the current time is treated as continuous data in a short time interval. In the previous square-residual related methods [13], [14], [15], [16], [17], [18], [19], [20], once the residual between the predicted and the measured distance value is larger than a threshold, the measured distance is detected as a NLOS measurement. However, the square residual between the estimated distance and the measured distance is usually overestimated or underestimated when the knowledge of user location estimation cannot be updated on time.…”

“…When the TDOA measurement from the i th LM is simulated to be biased by an NLOS error, we added a distribution to the true measurement represent for an NLOS error. If we consider the NLOS error as a random variable, a simple way to model it is to use the Gaussian distribution with mean nlos and variance 2 nlos [17]. For the purpose of simulation, the NLOS error is set as Gaussian distribution N(0, 5 2 ).…”

“…Mitigating NLOS measurements has attracted a lot of attention and several optimization algorithms have been proposed [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]. Broadly speaking, the literature on the NLOS problem falls under two categories: NLOS identification [13], [14] and NLOS mitigation [15], [16], [17], [18], [19], [20], [21].…”

“…Broadly speaking, the literature on the NLOS problem falls under two categories: NLOS identification [13], [14] and NLOS mitigation [15], [16], [17], [18], [19], [20], [21]. The former deals with mi-li@kddilabs.jp the problem of distinguishing between LOS and NLOS range information, whereas the latter typically deals with the reduction of the adverse impact of NLOS range errors on the accuracy of location estimates, assuming that the NLOS range estimates have been identified.…”

“…The noise covariance generated by an NLOS error is compensated only when the measured range data is smaller than the estimated range data. Several statistical NLOS-identification techniques [12], [13], [14], [15], [16], [17], [18], [19], [20], [21] for TDOA/ time of arrival (TOA) systems have been discussed previously, which exploit prior knowledge of NLOS delays and a series of measurements to reduce the bias in NLOS range estimates. NLOS detection measurements results indicate that when the square residual between the estimated distance and the measured distance cannot be updated on time, usually overestimate or underestimate of the measurement happens.…”