Calibration-Free Single-Anchor Indoor Localization Using an ESPAR Antenna

In this paper, we present a novel, low-cost approach to indoor localization that is capable of performing localization processes in real indoor environments and does not require calibration or recalibration procedures. To this end, we propose a single-anchor architecture and design based on an electronically steerable parasitic array radiator (ESPAR) antenna and Nordic Semiconductor nRF52840 utilizing Bluetooth Low Energy (BLE) protocol. The proposed algorithm relies on received signal strength (RSS) values measured by the receiver equipped with the ESPAR antenna for every considered antenna radiation pattern. The calibration-free concept is achieved by using inexpensive BLE nodes installed in known positions on the walls of the test room and acting as reference nodes for the positioning algorithm. Measurements performed in the indoor environment show that the proposed approach can successfully provide positioning results better than those previously reported for single-anchor ESPAR antenna localization systems employing the classical fingerprinting method and relying on time-consuming calibration procedures.

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Indoor Positioning Method Based on Infrared Vision and UWB Fusion

Journal of Physics Conference Series ◽

10.1088/1742-6596/2078/1/012070 ◽

2021 ◽

Vol 2078 (1) ◽

pp. 012070

Author(s):

Qianrong Zhang ◽

Yi Li

Keyword(s):

Real Time ◽

Indoor Localization ◽

Low Cost ◽

Ultra Wideband ◽

Coverage Area ◽

Positioning Accuracy ◽

Mobile Vehicle ◽

Positioning Method ◽

Positioning Algorithm ◽

Infrared Vision

Abstract Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.

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Indoor Localization System Using Wireless Sensor Network

Iraqi Journal of Computer Communication Control and System Engineering ◽

10.33103/uot.ijccce.18.1.3 ◽

2018 ◽

pp. 29-38

Keyword(s):

Indoor Localization ◽

Low Cost ◽

Wide Band ◽

Human Movement ◽

Indoor Positioning ◽

Positioning System ◽

Wireless System ◽

Anchor Nodes ◽

Indoor Positioning System ◽

Better Than

Building a precise low cost indoor positioning and navigation wireless system is a challenging task. The accuracy and cost should be taken together into account. Especially, when we need a system to be built in a harsh environment. In recent years, several researches have been implemented to build different indoor positioning system (IPS) types for human movement using wireless commercial sensors. The aim of this paper is to prove that it is not always the case that having a larger number of anchor nodes will increase the accuracy. Two and three anchor nodes of ultra-wide band with or without the commercial devices (DW 1000) could be implemented in this work to find the Localization of objects in different indoor positioning system, for which the results showed that sometimes three anchor nodes are better than two and vice versa. It depends on how to install the anchor nodes in an appropriate scenario that may allow utilizing a smaller number of anchors while maintaining the required accuracy and cost.

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Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Sci ◽

10.3390/sci2010007 ◽

2020 ◽

Vol 2 (1) ◽

pp. 7 ◽

Cited By ~ 2

Author(s):

Mickaël Delamare ◽

Remi Boutteau ◽

Xavier Savatier ◽

Nicolas Iriart

Keyword(s):

Motion Capture ◽

Indoor Environment ◽

Indoor Localization ◽

Ground Truth ◽

Industrial Applications ◽

Ultra Wideband ◽

Complex Environments ◽

Experimental Protocol ◽

Localization Systems ◽

Do So

Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments. In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

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Utilization of an OLED-Based VLC System in Office, Corridor, and Semi-Open Corridor Environments

Sensors ◽

10.3390/s20236869 ◽

2020 ◽

Vol 20 (23) ◽

pp. 6869

Author(s):

Zahra Nazari Chaleshtori ◽

Zabih Ghassemlooy ◽

Hossien B. Eldeeb ◽

Murat Uysal ◽

Stanislav Zvanovec

Keyword(s):

Indoor Localization ◽

Low Cost ◽

Flexible Substrate ◽

Path Loss ◽

Visual Display ◽

Outer Wall ◽

Channel Gain ◽

Delay Spread ◽

Indoor Environments ◽

Visible Light Communications

Organic light emitting diodes (OLEDs) have recently received growing interest for their merits as soft light and large panels at a low cost for the use in public places such as airports, shopping centers, offices, and train or bus stations. Moreover, the flexible substrate-based OLEDs provide an attractive feature of having curved or rolled lighting sources for the use in wearable devices and display panels. This technology can be implemented in visible light communications (VLC) for several applications such as visual display, data communications, and indoor localization. This article aims to investigate the use of flexible OLED-based VLC in indoor environments (i.e., office, corridor and semi-open corridor in shopping malls). We derive a two-term power series model to be match with the root-mean-square delay spread and optical path loss (OPL). We show that, for OLED positioned on outer-wall of shops, the channel gain is enhanced in contrast to them being positioned on the inner-wall. Moreover, the channel gain in empty environments is higher compare with the furnished rooms. We show that, the OPL for a 10 m link span are lower by 4.4 and 6.1 dB for the empty and semi-open corridors compared with the furnished rooms, when OLED is positioned on outer-wall of shops. Moreover, the channel gain in the corridor is higher compared with the semi-open corridor. We also show that, in furnished and semi-open corridors the OPL values are 55.6 and 57.2 dB at the center of corridor increasing to 87.6 and 90.7 dB at 20 m, respectively, when OLED is positioned on outer-wall of shops.

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Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Sci ◽

10.3390/sci1030062 ◽

2019 ◽

Vol 1 (3) ◽

pp. 62 ◽

Cited By ~ 2

Author(s):

Mickael Delamare ◽

Remi Boutteau ◽

Xavier Savatier ◽

Nicolas Iriart

Keyword(s):

Motion Capture ◽

Indoor Environment ◽

Indoor Localization ◽

Ground Truth ◽

Industrial Applications ◽

Ultra Wideband ◽

Complex Environments ◽

Experimental Protocol ◽

Localization Systems ◽

Do So

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Bandwidth Enhancement of a Bell-shaped UWB Antenna for Indoor Localization Systems

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.3975 ◽

2021 ◽

Vol 11 (1) ◽

pp. 6691-6695

Author(s):

M. S. Karoui ◽

N. Ghariani ◽

M. Lahiani ◽

H. Ghariani

Keyword(s):

Indoor Localization ◽

Low Cost ◽

Ground Plane ◽

Wide Band ◽

Impedance Bandwidth ◽

Uwb Antenna ◽

Simple Method ◽

Bandwidth Enhancement ◽

Measured Impedance ◽

Localization Systems

In this paper, a simple method of enhancing the bandwidth of the Bell-shaped UWB Antenna for indoor localization systems is proposed. Therefore, a modified version of the bell-shaped Ultra-Wide Band (UWB) antenna for indoor localization systems is presented. The proposed antenna is printed on a low-cost FR-4 substrate of 21×27×1.6mm3 size. It is composed of a bell-shaped radiating patch and a multi-slotted ground plane. The measured results show that the proposed antenna has an impedance bandwidth of about 11.2GHz ranging from 3.16GHz to 14.36GHz at S11<−10dB. Compared to the original version, an enhancement of about 5.56GHz in the measured impedance bandwidth was observed.

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User Localization in an Indoor Environment by Combining Different Algorithms through Plurality Rule

Journal of Intelligent Systems with Applications ◽

10.54856/jiswa.202012118 ◽

2020 ◽

pp. 64-68

Author(s):

Muzaffer Cem Ates ◽

Osman Emre Gumusoglu ◽

Aslinur Colak ◽

Nilgun Fescioglu Unver

Keyword(s):

Indoor Environment ◽

Indoor Localization ◽

Electoral System ◽

Plurality Rule ◽

Accurate Information ◽

Classification Algorithms ◽

Accuracy Rate ◽

Voting Rule ◽

Accuracy Rates ◽

Better Than

User localization in an indoor environment has a wide application area including production and service systems such as factories, smart homes, hospitals, nursing homes, etc. User localization based on Wi-Fi signals has been widely studied using various classification algorithms. In this type of problem, several Wi-Fi routers placed in an indoor environment provide signals with different strengths depending on the location/room of the user. Most classification algorithms successfully make the localization with a high accuracy rate. However, in the current literature, there is no widely accepted 'best' algorithm for solving this problem. This study proposes the use of the plurality rule to combine several classification algorithms and obtain a single result. Plurality voting rule is an electoral system where the candidate that polls the most vote wins the election. We apply the plurality rule to the indoor localization problem and generate the Majority algorithm. The Majority algorithm takes the 'votes' of five different classification algorithms and provides a single result through plurality rule. Results show that the mean accuracy rate of the Majority algorithm is higher than the classification algorithms it combines. In addition, we show that proving a single accuracy rate is not sufficient for declaring that an algorithm is better than the other. Classification algorithms select the training and test data randomly and different divisions result in different accuracy rates. In this study, we show that comparing the classification algorithms through confidence intervals provides more accurate information.

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Received signal strength–based localization for large space indoor environments

International Journal of Distributed Sensor Networks ◽

10.1177/1550147716686576 ◽

2017 ◽

Vol 13 (1) ◽

pp. 155014771668657 ◽

Cited By ~ 5

Author(s):

Xingwang Wang ◽

Xiaohui Wei ◽

Yuanyuan Liu ◽

Shang Gao

Keyword(s):

Indoor Environment ◽

Indoor Localization ◽

Sensor Data ◽

Indoor Environments ◽

Large Space ◽

Research Attention ◽

Novel Approach ◽

Strength Based ◽

Space Environments ◽

Space Layout

WiFi-based indoor localization has attracted recent research attention. Large space layout is a special and more complex indoor environment. Most existing indoor localization methods lead to poor accuracy and many of them are not suitable for large space environments. In this article, we propose a novel approach for indoor localization and navigation. In our approach, the expensive training is avoided by utilizing the concept of pre-scheduled path and automatically mapping the WiFi fingerprints to it. For online tracing, we utilize historical sensor data to delineate users’ trajectory and calculate the similarity to all possible paths on the map, then the system chooses the most similar one as the result. The proposed work is evaluated and compared with previous methods. The results show that our approach improves accuracy by 80%.

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INDOOR LIDAR RELOCALIZATION BASED ON DEEP LEARNING USING A 3D MODEL

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b1-2020-541-2020 ◽

2020 ◽

Vol XLIII-B1-2020 ◽

pp. 541-547

Author(s):

H. Zhao ◽

D. Acharya ◽

M. Tomko ◽

K. Khoshelham

Keyword(s):

Indoor Environment ◽

3D Model ◽

Indoor Localization ◽

High Accuracy ◽

Lidar Data ◽

Indoor Environments ◽

Navigation Systems ◽

Range Image ◽

Range Images ◽

Mapping Systems

Abstract. Indoor localization, navigation and mapping systems highly rely on the initial sensor pose information to achieve a high accuracy. Most existing indoor mapping and navigation systems cannot initialize the sensor poses automatically and consequently these systems cannot perform relocalization and recover from a pose estimation failure. For most indoor environments, a map or a 3D model is often available, and can provide useful information for relocalization. This paper presents a novel relocalization method for lidar sensors in indoor environments to estimate the initial lidar pose using a CNN pose regression network trained using a 3D model. A set of synthetic lidar frames are generated from the 3D model with known poses. Each lidar range image is a one-channel range image, used to train the CNN pose regression network from scratch to predict the initial sensor location and orientation. The CNN regression network trained by synthetic range images is used to estimate the poses of the lidar using real range images captured in the indoor environment. The results show that the proposed CNN regression network can learn from synthetic lidar data and estimate the pose of real lidar data with an accuracy of 1.9 m and 8.7 degrees.

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Utilization of a Non-Linear Error Function in a Positioning Algorithm for Distance Measurement Systems Designed for Indoor Environments

Journal of Sensor and Actuator Networks ◽

10.3390/jsan8020021 ◽

2019 ◽

Vol 8 (2) ◽

pp. 21

Author(s):

Agnieszka Czapiewska

Keyword(s):

Indoor Environment ◽

Error Function ◽

Measurement Data ◽

Distance Measurement ◽

Indoor Environments ◽

Comparative Performance ◽

Positioning Accuracy ◽

Measurement Systems ◽

Non Linear ◽

Positioning Algorithm

A new positioning algorithm for distance measurement systems is outlined herein. This algorithm utilizes a non-linear error function which allows us to improve the positioning accuracy in highly difficult indoor environments. The non-linear error function also allows us to adjust the performance of the algorithm to the particular environmental conditions. The well-known positioning algorithms have limitations, mentioned by their authors, which make them unsuitable for positioning in an indoor environment. In this article, there is a brief discussion about the most popular positioning algorithms with consideration of the indoor environment. The new positioning algorithm is described in detail and a comparative performance analysis of the well-known algorithms and the proposed one is conducted. Those research results are achieved with the utilization of real distance measurement data, collected inside a few different buildings, and they show that the proposed algorithm outperforms the Chan and Foy algorithms in indoor environments. In this article the Automatic Person Localization System (SALOn) is also presented, which was utilized to collect measurement data.

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