In this paper, we present a selective hybrid weighting approach to intra cell locate a mobile station (MS) when both the range and the angle measurements are corrupted and NonLine-of-Sight (NLOS) are not identified from Line-of-Sight (LOS) measurements. The NLOS effects are minimized by means of proper range scaling use and AOA to the base station correction. The MS location is estimated using weighted ranges and angular beam which produce special points, called potential points. The performance comparisons of the proposed method to other hybrid location methods are investigated in the NLOS environment. It is found that the proposed method can deal with NLOS error effectively making it attractive for location estimation in cellular networks.

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We address the problem of line of sight/no line of sight (LOS/NLOS) identification in a hybrid context where received signal strength and angle of arrival (RSS/AOA) measurements are combined. Two approaches are proposed, which aim to mitigate the range bias introduced by NLOS propagation. First, a hybrid hypothesis test (HHT) is proposed whose aim is to identify the most probable two Base Stations (BSs) to be LOS. The HHT considers an error function incorporating both RSS and AOA measurements. If the HHT succeeds in identifying two LOS BSs, then it directly proceeds to localisation. Otherwise, the HHT identifies, the two least probable BSs to be NLOS, over which a weighting approach will be applied. The weighting indeed serves to attenuate at a some degree, the NLOS propagation effect and then correct the location. In the first scenario, NLOS are completely discarded, whereas in the second one, their effect is attenuated, thus improving the location accuracy in both cases. Simulations results corroborate the expected performance enhancement. Fundamental performance limits for the localisation accuracy based on such hybrid measurements are evaluated through the corresponding Cramer–Rao lower bound. Copyright © 2015 John Wiley & Sons, Ltd.

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