A Hybrid Indoor Positioning System Using a Linear Weighted Policy Learner and Iterative PDR

Simões, Walter Charles Sousa Seiffert; Silva, Walmir Acioli E.; Lucena, Mateus Martínez De; Jazdi, Nasser; Lucena, Vicente Ferreira de

doi:10.1109/access.2020.2977501

Cited by 7 publications

(5 citation statements)

References 47 publications

(148 reference statements)

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“…In order to achieve 3D positioning in multiple scenes, many studies have been undertaken, including studies in specific positioning environments. Some researchers first narrowed the localization scope and found a possible solution interval [10]. In scenarios where 3D positioning needs to be acquired, researchers have improved the dispersion of the base station in the altitude direction [11][12][13][14].…”

Section: Advanced Researchmentioning

confidence: 99%

“…Newton's method was chosen to iteratively calculate the value of the unknown point, and the method can converge correctly in the x and y directions by taking into account the calculation of the height of the near-plane deployment. The solution space for the mobile station location is: (10) The superscript ∼ indicates the true value. There are two extreme-value points for the objective function in the solution space:…”

Section: Iterative Initial Value Selectionmentioning

confidence: 99%

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An Indoor UWB 3D Positioning Method for Coplanar Base Stations

Zhou

et al. 2022

Sensors

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As an indispensable type of information, location data are used in various industries. Ultrawideband (UWB) technology has been used for indoor location estimation due to its excellent ranging performance. However, the accuracy of the location estimation results is heavily affected by the deployment of base stations; in particular, the base station deployment space is limited in certain scenarios. In underground mines, base stations must be placed on the roof to ensure signal coverage, which is almost coplanar in nature. Existing indoor positioning solutions suffer from both difficulties in the correct convergence of results and poor positioning accuracy under coplanar base-station conditions. To correctly estimate position in coplanar base-station scenarios, this paper proposes a novel iterative method. Based on the Newton iteration method, a selection range for the initial value and iterative convergence control conditions were derived to improve the convergence performance of the algorithm. In this paper, we mathematically analyze the impact of the localization solution for coplanar base stations and derive the expression for the localization accuracy performance. The proposed method demonstrated a positioning accuracy of 5 cm in the experimental campaign for the comparative analysis, with the multi-epoch observation results being stable within 10 cm. Furthermore, it was found that, when base stations are coplanar, the test point accuracy can be improved by an average of 63.54% compared to the conventional positioning algorithm. In the base-station coplanar deployment scenario, the upper bound of the CDF convergence in the proposed method outperformed the conventional positioning algorithm by about 30%.

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Section: Advanced Researchmentioning

confidence: 99%

Section: Iterative Initial Value Selectionmentioning

confidence: 99%

An Indoor UWB 3D Positioning Method for Coplanar Base Stations

Zhou

et al. 2022

Sensors

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“…Whereas vision, inertial navigation and radio-frequency (RF) based data processing solutions coexist in hybrid systems with the pervasiveness of smart phones [12], low power consumption and low processing requirements make the pure RF based systems preferable. Wi-Fi technology is one of the oldest RF technologies used for indoor positioning because of its easy-to-use and already installed infrastructure for accessing local networks.…”

Section: A Indoor Positioningmentioning

confidence: 99%

Adaptive Sequential Monte Carlo Filter for Indoor Positioning and Tracking With Bluetooth Low Energy Beacons

2021

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We model the tracking of Bluetooth low-energy (BLE) transmitters as a three layer hidden Markov model with joint state and parameter estimation. We are after a filtering distribution by Bayesian approximation using Monte Carlo sampling techniques. In a test environment decorated with multiple BLE sensors, the tracking relies only on the naturally unreliable received signal strength indicator (RSSI) of the captured signals. We assume that the tracked BLE transmitter does not provide any other motion or position related information. Hence, the transition density is designed to be merely a diffusion where the probability measures are diffused into the neighboring space. This makes the diagonal error covariance factor of the prediction density, namely the diffusion factor, the most important parameter to be tuned on the fly. We first show an experimental proof of concept using synthetic data on real trajectories by comparing three parameter estimation approaches: static, decaying and adaptive diffusion factors. We then obtain the results on real data which show that online parameter sampling adapts to the observed data and yields lower error means and medians, but more importantly steady error distributions with respect to a large range of parameters. INDEX TERMS Bluetooth low-energy, indoor positioning and tracking, parameter estimation, sequential Monte Carlo, wasserstein interpolation

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“…Simões et al formed a research group on the location and indoor navigation of people with visual impairments [ 128 , 129 ]. The group’s two main research objectives were: to combine techniques and technologies to create records of reference sites to be used in the development of navigation routes and to create safety perimeters around the user to avoid collisions with obstacles.…”

Section: Comparison Of Systems Discussedmentioning

confidence: 99%

“…They adopted a technique called Linear Weighted Policy Learner (LWPL), which takes advantage of the characteristics of the Weighted Policy Learner (WPL) algorithm. Still, it introduces a linearization of its formulations to consume less time and processing [ 129 ]. Each record is the result of the fusion of data from Wi-Fi signals (RSSI), inertial sensors, and images (computer vision).…”

Section: Comparison Of Systems Discussedmentioning

confidence: 99%

A Review of Technologies and Techniques for Indoor Navigation Systems for the Visually Impaired

Simões

Machado

Sales

et al. 2020

Sensors

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Technologies and techniques of location and navigation are advancing, allowing greater precision in locating people in complex and challenging conditions. These advances have attracted growing interest from the scientific community in using indoor positioning systems (IPSs) with a higher degree of precision and fast delivery time, for groups of people such as the visually impaired, to some extent improving their quality of life. Much research brings together various works that deal with the physical and logical approaches of IPSs to give the reader a more general view of the models. These surveys, however, need to be continuously revisited to update the literature on the features described. This paper presents an expansion of the range of technologies and methodologies for assisting the visually impaired in previous works, providing readers and researchers with a more recent version of what was done and the advantages and disadvantages of each approach to guide reviews and discussions about these topics. Finally, we discuss a series of considerations and future trends for the construction of indoor navigation and location systems for the visually impaired.

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A Hybrid Indoor Positioning System Using a Linear Weighted Policy Learner and Iterative PDR

Cited by 7 publications

References 47 publications

An Indoor UWB 3D Positioning Method for Coplanar Base Stations

An Indoor UWB 3D Positioning Method for Coplanar Base Stations

Adaptive Sequential Monte Carlo Filter for Indoor Positioning and Tracking With Bluetooth Low Energy Beacons

A Review of Technologies and Techniques for Indoor Navigation Systems for the Visually Impaired

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