Multi-Step Optimization of Indoor Localization Accuracy Using Commodity WiFi

Li, Shuyu; Welsen, Sherif; Brusic, Vladimir

doi:10.1109/pimrc50174.2021.9569286

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…We extended the original single-AP localization algorithm [ 33 ], implemented it for a multi-AP solution, and proposed a novel adaptive localization algorithm with a low computational cost. The median localization accuracy was improved by ∼20% by an unbiased combination of three APs as compared to the best individual AP localization.…”

Section: Discussionmentioning

confidence: 99%

“…Here, we report a new adaptive joint localization algorithm. A detailed description of MoLA is available in [ 33 ]. This section provides a brief description of MoLA.…”

Section: Mola: Design and Optimizationmentioning

confidence: 99%

“…We previously developed MoLA, a Multi-step Optimization Localization Algorithm, and compared the performance of MoLA and SpotFi for a single AP. We showed that the multi-step optimization used in MoLA improved the median accuracy of indoor localization as compared with SpotFi (0.96 m vs. 1.93 m) in the test space [ 33 ]. To enable further comparisons and encourage knowledge sharing, we provided MoLA to the community as open-source [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

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Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization

Welsen

Brusic

2022

Sensors

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WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival (AoA) based, and they deploy the conventional MUSIC algorithm. The localization accuracy can be achieved by algorithm improvements or joint localization that deploys multiple Access Points (APs). We performed an experiment that assessed the Test Point (TP) accuracy and distribution of results in a complex environment. The testing space was a 290 m2 three-room environment with three APs with 38 TPs. The joint localization using three APs was performed in the same test space. We developed and implemented a new algorithm for improved accuracy of joint localization. We analyzed the statistical characteristics of the results based on each TP and show that the local space-dependent factors are the key factors for localization accuracy. The most important factors that cause errors are distance, obstacles, corner locations, the location of APs, and the angular orientation of the antenna array. Compared with the well-known SpotFi algorithm, we achieved a mean accuracy (across all TPs) improvement of 46%. The unbiased joint localization median accuracy improved by 20% as compared to the best individual localization.

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Section: Discussionmentioning

confidence: 99%

“…Here, we report a new adaptive joint localization algorithm. A detailed description of MoLA is available in [ 33 ]. This section provides a brief description of MoLA.…”

Section: Mola: Design and Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization

Welsen

Brusic

2022

Sensors

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“…For this purpose, we can use a method suitable for smooth, unconstrained optimization, for example first-order or second-order methods, where the inequality constraints are subject to a quadratic penalty. The solution proposed in this paper applied the gradient method (first-order method) and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm (second-order method) [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Adjusting products with compensatory elements using a digital twin: Model and methodology

Konecny

Bailova²,

Beremlijski³

et al. 2023

PLoS ONE

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The article presents a novel strategy for reducing the geometric error of a vehicle headlamp equipped with a set of calibration screws, which represents a product assembly. Using a general method for designing and implementing a digital twin, we determined the optimal configuration for a compensatory element that minimizes the total geometric error. Formulated as a problem of constrained minimization, we solved the error using the gradient method and the Broyden–Fletcher–Goldfarb–Shanno method. Products are automatically adjusted according to this optimal setting during the manufacturing process. The results of this novel method indicate that all points can be aligned when the non-individual calibration satifies a geometrical specification of 92%. The digital twin approach was compared to the manufacturing process on 84,055 samples. Overall, 98.19% of the samples were perfectly aligned.

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