Mobile Location Estimator in Mixed LOS/NLOS Conditions Using UKF Banks
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In wireless mobile location systems, NLOS problem has been considered as the key issue that affects the estimation accuracy. In this paper, mobile location in a mixed line-of-sight/non-line-of-sight (LOS/NLOS) condition is considered, and a NLOS error mitigation technique is proposed, which utilizes unscented Kalman filter (UKF) to jointly estimate mobile state and the hidden sight state based on the data collected by each BS. In addition, data fusion method is further applied to achieve high estimation accuracy. Simulation results demonstrate that the performance of the proposed method meet the requirement of the FCC E911 in different LOS/NLOS conditions.Keywords:
Non-line-of-sight propagation
One of the major challenges to finding accurate mobile terminal location is the non-line-of-sight (NLOS) propagation caused by the blocking of the signal's direct path by obstacles. Traditional location algorithms perform poorly in NLOS environments and this has made it necessary to develop techniques to identify NLOS transmissions and then employ suitable error mitigation techniques. It is extremely difficult to characterize NLOS error because it varies with time and is location specific. We present statistical based techniques to distinguish LOS and NLOS propagation for various scenarios and present simulation results to validate them.
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Blocking (statistics)
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Based on the statistical property of the non-line-of-sight(NLOS)propagation in cellular networks and the line-of-sight(LOS)reconstruction /smoothing algorithm,an improved location method is presented to mitigate the influence of the NLOS propagation.First,the mean and variance of the NLOS propagation delay are estimated using the statistical property of the NLOS propagation delay;and then the measurements of time difference of arrival(TDOA)are modified to estimate the location of mobile station(MS);finally,the locations of the MS of different time are weighted to further mitigate the influence of the NLOS propagation.The simulation results prove that the proposed method can improve the location accuracy of the location algorithm effectively.
Non-line-of-sight propagation
Smoothing
Time of arrival
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The location of mobile terminals has received considerable attention in the recent years. The performance of mobile location systems is limited by errors primarily caused by nonline-of-sight (NLOS) propagation conditions. In this paper, we investigate the NLOS error identification and correction techniques for mobile user location in wireless cellular systems. Based on how much a priori knowledge of the NLOS error is available, two NLOS mitigation algorithms are proposed. Simulation results demonstrate that, with the prior information database, the location estimate can he obtained with good accuracy even in severe NLOS propagation conditions.
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Ultra-wideband (UWB) is a promising indoor position technology with centimetre-level positioning accuracy in line-of-sight (LOS) situations. However, walls and other obstacles are common in an indoor environment, which can introduce non-line-of-sight (NLOS) and deteriorate UWB positioning accuracy to the meter level. This paper proposed a succinct method to identify NLOS induced by walls and mitigate the error for improved UWB positioning with NLOS. First, NLOS is detected by a sliding window method, which can identify approximately 90% of NLOS cases in a harsh indoor environment. Then, a delay model is designed to mitigate the error of the UWB signal propagating through a wall. Finally, all the distance measurements, including LOS and NLOS, are used to calculate the mobile UWB tag position with ordinary least squares (OLS) or weighted least squares (WLS). Experiment results show that with correct NLOS indentation and delay model, the proposed method can achieve positioning accuracy in NLOS environments close to the level of LOS. Compared with OLS, WLS can further optimise the positioning results. Correct NLOS indentation, accurate delay model and proper weights in the WLS are the keys to accurate UWB positioning in NLOS environments.
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Identifying non-line-of-sight (NLOS) conditions is important to discard, or improve, any location estimates that have been estimated with NLOS ranges. Typically, NLOS identification relies on channel statistics that have been collected for both LOS and NLOS channels. We investigate NLOS identification using distance residuals instead. The results show that distance residuals can be used to identify location estimates with NLOS ranges with very high accuracy, and that in some cases, individual NLOS ranges can also be identified.
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Non-line-of-sight (NLOS) error is the most common and also a major source of errors in wireless location system. This paper presents an approach to ameliorate the effect of the NLOS using Time Difference Of Arrival (TDOA) with more than minimum number of base stations (BSs). This algorithm makes use of the redundant TDOA measurements to formulate a problem as a test of hypothesis in order to get a hard decision to discard the NLOS-BSs, comparing with one certain ratio proposed in this paper, and it has no use for the distributing probability of the NLOS noise. Numerical simulations show that the proposed algorithm can completely discard the NLOS-BSs when NLOS error is higher than the measurement noise.
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The majority of the location estimation error in wireless communication systems comes from the effect of non-line-of-sight (NLOS) propagation. NLOS identification and correction are the main techniques of mitigating the NLOS impact on positioning accuracy. In this paper, we propose a cooperative localization algorithm that combines the hybrid time of arrival (TOA) / angle of arrival (AOA) measurements of all identified Line-of-Sight (LOS) base station (BS) - mobile station (MS) links with the TOA measurements of MS-MS links. Different cost functions are described according to the NLOS detection results based on existing identification methods. A NLOS correction model is also presented when the destination MS to be located is completely in NLOS propagation, whereas some BS - cooperative MS links are in LOS conditions. Simulation results demonstrate that the proposed algorithm outperforms other existing hybrid localization techniques, and its accuracy increases with the number of LOS BS-MS links, as well as the NLOS detection accuracy.
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This paper presents ultra wideband (UWB) off-body radio channel characterisation for both line-of-sight (LOS) and non-line-of-sight (NLOS) communication scenarios. Measurement campaigns were performed in the indoor environment using UWB wireless active tags. The path loss of nine different off-body radio channels for LOS and NLOS communication scenarios is shown and analysed. Results show that maximum of 13.62 dB higher path loss of off-body channel is noticed for NLOS communication scenario in compare to (LOS). A least square fit method was performed on the measured path loss results for both LOS and NLOS cases. Increase of 32.17% path loss exponent is noticed for the NLOS scenario.
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It is well known that location accuracy is low in non-line-of-sight (NLOS) scenarios. Several techniques have been proposed to mitigate ranging errors to improve location accuracy. These techniques play an important role in accurate localization for many applications which target safety and productivity in harsh industrial environments. In some cases, these mitigation techniques target specific NLOS scenarios, therefore such scenarios have to identified before mitigation can be applied. In this paper, we study identification of two types of NLOS scenarios that are common indoors: Through-the-Wall (TTW) and Around-the-Corner (ATC). We conduct a measurement campaign in various indoor TTW and ATC scenarios, and show that these two types of NLOS scenarios can be differentiated with high accuracy using channel statistics from ultra-wideband radios.
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