Approximate Maximum Likelihood Mobile Localization using Scatterer Information

Zhaounia, Mohamed; Landolsi, Mohamed Adnan; Bouallègue, Ridha

doi:10.1109/vetecs.2009.5073405

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Techniques coping with NLOS errors for wireless location can be categorised into three different types. The first type models the propagation parameters of the channel by a scattering model further used to localise the MS . The second type identifies the LOS BSs by using history‐based hypothesis testing .…”

Section: Introductionmentioning

confidence: 99%

Hybrid RSS/AOA hypothesis test for NLOS/LOS base station discrimination and location error mitigation

Gazzah

Najjar

Besbes

2015

Trans. Emerging Tel. Tech.

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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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Section: Introductionmentioning

confidence: 99%

Hybrid RSS/AOA hypothesis test for NLOS/LOS base station discrimination and location error mitigation

Gazzah

Najjar

Besbes

2015

Trans. Emerging Tel. Tech.

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“…Although it provides good performance when direct paths between the BSs and the Ms are available, the proposed HAML algorithm fails in NLoS environments. For this purpose, in [23], we proposed a new technique that adapts the HAML method to NLoS environments using measurements exclusively from the serving BS and when the scatterers are exponentially distributed around the MS. In this paper, we present a generalization of the algorithm by proposing a more thorough description and including further scattering models and various number of BSs.…”

Section: Introductionmentioning

confidence: 99%

Mobile Localization Under Non-Line-of-Sight Conditions Using Scattering Information

Zhaounia¹,

Landolsi

Bouallègue³

2010

Int J Wireless Inf Networks

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A novel mobile localization algorithm under non-line-of-sight (NLoS) conditions involving at most two base stations (BS) is presented. By using such a small number of BSs, the proposed technique avoids problems related to weak mobile hearability and excessive network messaging overload. Based on a scattering model, the NLoS hybrid approximate maximum likelihood (NLoS HAML) approach presented herein estimates the distances between the mobile station (MS) and the scatterers through the measured hybrid time-of-arrival/angle-of-arrival (ToA/ AoA) statistics. Then, it matches the calculated distances to a known scatterers' distribution in a maximum likelihood (ML) sense. Numerical results prove that the proposed algorithm outperforms previous methods by providing an accuracy enhancement that reaches 60%. It is also shown that the performance enhancement provided by the proposed algorithm is maximized when the adequate scatterers distribution is adopted.

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