A novel scattering distance-based mobile positioning algorithm

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

doi:10.1109/giis.2009.5307099

Cited by 5 publications

(6 citation statements)

References 9 publications

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“…where 'R{}' takes the real part and the integral is taken over the area of the LIS, which we assume to have a disk-shape of radius R. Note that as CRLB scales down linearly in signal to noise ratio (SNR), we set N 0 = 2 throughout the paper to eliminate the scaling factor in (6).…”

Section: Signal Model With Lismentioning

confidence: 99%

“…For analytical tractability, we assume an ideal situation where no scatterers or reflections are present, yielding a perfect line-of-sight (LoS) propagation scenario and each terminal is assumed to radiate isotropically. Although we do not deal with more complicated geometries, our results are fundamental in the sense that positioning of objects in scattering environment [6], [7] is commonly done in two steps: i) estimating the positions of a number of reflecting objects in the environment, and ii) backward computation of the position of the object of interest. Therefore, our results are instrumental for the understanding of the accuracy in the first step.…”

Section: Introductionmentioning

confidence: 99%

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Cramér-Rao Lower Bounds for Positioning with Large Intelligent Surfaces

Rusek

Edfors

2017

2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)

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We consider the potential for positioning with a system where antenna arrays are deployed as a large intelligent surface (LIS). We derive Fisher-informations and Cramér-Rao lower bounds (CRLB) in closed-form for terminals along the central perpendicular line (CPL) of the LIS for all three Cartesian dimensions. For terminals at positions other than the CPL, closed-form expressions for the Fisher-informations and CRLBs seem out of reach, and we alternatively provide approximations (in closed-form) which are shown to be very accurate. We also show that under mild conditions, the CRLBs in general decrease quadratically in the surface-area for both the x and y dimensions. For the z-dimension (distance from the LIS), the CRLB decreases linearly in the surface-area when terminals are along the CPL. However, when terminals move away from the CPL, the CRLB is dramatically increased and then also decreases quadratically in the surface-area. We also extensively discuss the impact of different deployments (centralized and distributed) of the LIS.

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Section: Signal Model With Lismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cramér-Rao Lower Bounds for Positioning with Large Intelligent Surfaces

Rusek

Edfors

2017

2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)

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“…where ∆a ′ and ∆b ′ denote calculation errors. We then substitute (20) and (21) into (17) and square both sides. Eq.…”

Section: Threshold Derivationmentioning

confidence: 99%

“…Shu et al [19] proposed a weighted localization algorithm based on geographical constraints. In [20][21][22], to improve position estimation, the researchers pre-constructed several specified scattering models; however, the rapid-changing urban environment (i.e., appearance and disappearance of buildings) made it difficult to identify an accurate scattering model. In [23], the angle of departure (AOD) was used to identify the NLOS measurement as long as there were sufficient single reflected NLOS paths or the AOD could be measured at the MS. Theoretically, AOD methods can effectively mitigate the NLOS error; however, the single-reflection propagation model is not consistent with practical environments, and the AOD measurement in the MS does not have sufficient accuracy due to the array size limitation.…”

Section: Introductionmentioning

confidence: 99%

Geometry-based non-line-of-sight error mitigation and localization in wireless communications

Hua

Yin

Wang

et al. 2019

Sci. China Inf. Sci.

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Recently, positioning services have received considerable attention. The primary source of the positioning error is non-line-of-sight (NLOS) propagation. To address this problem, we propose a novel NLOS mitigation scheme, in which the geometric relationship between a base station and a mobile station is used. This makes it possible to identify range measurements corrupted by NLOS errors, and the mobile station can then estimate its position through line-of-sight (LOS) measurements. Moreover, the threshold of the NLOS detector is derived via a hybrid method using both the analytical derivation and computer simulation, which significantly reduces the difficulty of identifying thresholds. After identifying the NLOS measurements, a two-step weighted-least-squares algorithm is used to obtain the localization, in which both range and angle measurements are considered. The simulation results reveal that the proposed algorithm yields a high identification probability of NLOS measurements, which results in improved localization performance.

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“…With the help of angle measurement, two BSs location algorithm is presented in [11]. The work in [12] proposes the scattering distance-based algorithm with only one BS using the multipath. Therefore, it is meaningful work to extend the idea of Rwgh and IMR algorithm to adapt for limited BSs scenario.…”

Section: Introductionmentioning

confidence: 99%

Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network

Wang

2015

Wireless Pers Commun

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In a cellular network, a location scenario is considered in this paper, which the home base station (BS) measures the range and angle while neighboring BSs measure the ranges. Based on the range and angle measurements, two adaptive non-line-of-sight (NLOS) identification and mitigation location algorithms with low complexity are proposed. The main idea of our proposed algorithms is to search the optimal subset of range and angle measurements by utilizing the hybrid lines of position algorithm and comparing the normalized residual error to perform the NLOS identification and location. Compared with the existing algorithms, the proposed algorithms have three advantages: one is different to the existing algorithms that require at least three BSs, the proposed algorithms can be suitable for two BSs scenario. Second is the low complexity of our proposed algorithms compared with the existing algorithms. The last is simulation results show that the proposed algorithms outperform the existing algorithms in bad urban and urban environments.

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A novel scattering distance-based mobile positioning algorithm

Cited by 5 publications

References 9 publications

Cramér-Rao Lower Bounds for Positioning with Large Intelligent Surfaces

Cramér-Rao Lower Bounds for Positioning with Large Intelligent Surfaces

Geometry-based non-line-of-sight error mitigation and localization in wireless communications

Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network

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