scholarly journals A novel indoor localization scheme based on refined fingerprint-based autoencoder network

2018 ◽  
Vol 189 ◽  
pp. 03017
Author(s):  
Junhui Mei ◽  
Juntong Xi
Keyword(s):  
Indoor Localization ◽  
Low Cost ◽  
Access Point ◽  
Indoor Environments ◽  
Location Based Service ◽  
Accuracy Improvement ◽  
Positioning Systems ◽  
Localization Scheme ◽  
Environmental Properties ◽  
Indoor Scenes

Indoor positioning systems have attracted increasing interests for the emergency of location based service in indoor environments. Wi-Fi fingerprint-based localization scheme has become a promising indoor localization technique due to the availability of access point (AP) and its low cost. However, the received signal strength (RSS) values are easily fluctuated by the interference of multi-path effects, which introduce propagation errors into localization results. In order to address the issue, a fingerprint-based autoencoder network scheme is proposed to learn the essential features from the measured coarse RSS values and extract the trained weight parameters of autoencoder network as refined fingerprints. The extracted fingerprints are able to represent the environmental properties and display strong robustness with fluctuated signals. The proposed scheme is further implemented in complex indoor scenes, which substantiate the effectiveness and accuracy improvement compared with other RSS-based schemes.

scholarly journals Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Zahid Farid ◽  
Rosdiadee Nordin ◽  
Mahamod Ismail ◽  
Nor Fadzilah Abdullah
Keyword(s):  
Indoor Localization ◽  
Average Distance ◽  
Optimization Technique ◽  
Computational Time ◽  
Hybrid Technique ◽  
Indoor Environments ◽  
Positioning Systems ◽  
Accurate Localization ◽  
Hybrid Positioning ◽  
Localization Scheme

In indoor environments, WiFi (RSS) based localization is sensitive to various indoor fading effects and noise during transmission, which are the main causes of localization errors that affect its accuracy. Keeping in view those fading effects, positioning systems based on a single technology are ineffective in performing accurate localization. For this reason, the trend is toward the use of hybrid positioning systems (combination of two or more wireless technologies) in indoor/outdoor localization scenarios for getting better position accuracy. This paper presents a hybrid technique to implement indoor localization that adopts fingerprinting approaches in both WiFi and Wireless Sensor Networks (WSNs). This model exploits machine learning, in particular Artificial Natural Network (ANN) techniques, for position calculation. The experimental results show that the proposed hybrid system improved the accuracy, reducing the average distance error to 1.05 m by using ANN. Applying Genetic Algorithm (GA) based optimization technique did not incur any further improvement to the accuracy. Compared to the performance of GA optimization, the nonoptimized ANN performed better in terms of accuracy, precision, stability, and computational time. The above results show that the proposed hybrid technique is promising for achieving better accuracy in real-world positioning applications.

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

Sensors ◽  
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.

Accurate Dead Reckoning Localization System Using RFID Phase

2014 ◽  
Vol 513-517 ◽  
pp. 3296-3299 ◽  
Author(s):  
Bo Li ◽  
Dong Wang
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Dead Reckoning ◽  
Location Based Service ◽  
Rfid Tag ◽  
Whole Process ◽  
Localization Scheme ◽  
Frequency Identification ◽  
Series Of Experiments

Nowadays, the demands of Location-based Service are growing fast. It contains huge business opportunities. This paper presents an efficient indoor localization scheme using Radio-Frequency Identification technology. The major idea of our method is Dead Reckoning, a method of navigation that using the best estimates of speed and direction to calculate users' motion trace. We implemented Dead Reckoning in indoor environment by taking advantage of features of RFID. We collected RFID tag phase value to calculate the velocity of users and recalibrate users' position by using known fixed RFID reader. We designed a series of experiments to verify the feasibility of our velocity calculation method, then we simulated the whole process of our system. The results show that our system can track user's motion effectively in indoor environment. We believe this is an encouraging result, holding promise for real-world deployment.

scholarly journals PEOPLE’S PPRESENCE EFFECT ON WLAN-BASED IPS’ ACCURACY

2015 ◽  
Vol 77 (9) ◽  
Author(s):  
Iyad H Alshami ◽  
Noor Azurati Ahmad ◽  
Shamsul Sahibuddin
Keyword(s):  
Low Cost ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Positioning System ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Indoor Positioning System ◽  
Closed Environment ◽  
Presence Of People

In order to enable Location Based Service (LBS) closed environment, many technologies have been investigated to replace the Global Positioning System (GPS) in the localization process in indoor environments. WLAN is considered as the most suitable and powerful technology for Indoor Positioning System (IPS) due to its widespread coverage and low cost. Although WLAN Received Signal Strength Indicator (RSS) fingerprinting can be considered as the most accurate IPS method, this accuracy can be weakened due to WLAN RSS fluctuation. WLAN RSS fluctuates due to the multipath being influenced by obstacles presence. People presence under WLAN coverage can be considered as one of the main obstacles which can affect the WLAN-IPS accuracy. This research presents experimental results demonstrating that people’s presence between access point (AP) and mobile device (MD) reduces the received signal strength by -2dBm to -5dBm. This reduction in RSS can lead to distance error greater than or equal to 2m. Hence, any accurate IPS must consider the presence of people in the indoor environment. 

scholarly journals Support Vector Regression for Mobile Target Localization in Indoor Environments

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 358
Author(s):  
Satish R. Jondhale ◽  
Vijay Mohan ◽  
Bharat Bhushan Sharma ◽  
Jaime Lloret ◽  
Shashikant V. Athawale
Keyword(s):  
Support Vector Regression ◽  
Target Location ◽  
Indoor Localization ◽  
Target Localization ◽  
Superior Performance ◽  
Support Vector ◽  
Generalized Regression Neural Network ◽  
Indoor Environments ◽  
Localization Scheme ◽  
Mobile Target

Trilateration-based target localization using received signal strength (RSS) in a wireless sensor network (WSN) generally yields inaccurate location estimates due to high fluctuations in RSS measurements in indoor environments. Improving the localization accuracy in RSS-based systems has long been the focus of a substantial amount of research. This paper proposes two range-free algorithms based on RSS measurements, namely support vector regression (SVR) and SVR + Kalman filter (KF). Unlike trilateration, the proposed SVR-based localization scheme can directly estimate target locations using field measurements without relying on the computation of distances. Unlike other state-of-the-art localization and tracking (L&T) schemes such as the generalized regression neural network (GRNN), SVR localization architecture needs only three RSS measurements to locate a mobile target. Furthermore, the SVR based localization scheme was fused with a KF in order to gain further refinement in target location estimates. Rigorous simulations were carried out to test the localization efficacy of the proposed algorithms for noisy radio frequency (RF) channels and a dynamic target motion model. Benefiting from the good generalization ability of SVR, simulation results showed that the presented SVR-based localization algorithms demonstrate superior performance compared to trilateration- and GRNN-based localization schemes in terms of indoor localization performance.

Beacon selection and calibration for the efficient localization of a mobile robot

Robotica ◽  
2013 ◽  
Vol 32 (1) ◽  
pp. 115-131 ◽  
Author(s):  
Jaehyun Park ◽  
Jangmyung Lee
Keyword(s):  
Mobile Robot ◽  
Indoor Localization ◽  
Setup Time ◽  
Ultrasonic Waves ◽  
Mobile Robot Navigation ◽  
Indoor Environments ◽  
Ultrasonic Sensors ◽  
Indoor Space ◽  
Localization Scheme ◽  
Set Up

SUMMARYThis paper proposes a localization scheme using ultrasonic beacons in an unstructured multi-block workspace. Indoor localization schemes using ultrasonic sensors have widely been studied due to their low costs and high accuracies. However, ultrasonic sensors are susceptible to environmental noise due to the propagation characteristics of ultrasonic waves. In addition, the decay of ultrasonic signals over long distances implies that ultrasonic sensors are unsuitable for use in large indoor environments. To overcome these shortcomings of ultrasonic sensors, while retaining their advantages, a multi-block approach was devised by dividing an indoor space into several blocks with multiple beacons in each block. However, it is difficult to divide an indoor space into several blocks when beacons cannot be installed in a regular manner or when some new beacons are installed. To resolve this difficulty, a dynamic algorithm is needed to divide an indoor space into multiple blocks and to select suitable beacons. Therefore, this paper proposes a real-time localization scheme to estimate the position of a mobile robot independent of beacon locations and to estimate the position of a new beacon installed at an unknown position. A beacon selection algorithm was developed to select optimal beacons according to robot position and to set up sets of beacons for mobile robot navigation. By using the new beacon searching and calibration algorithm, a mobile robot is able to navigate in an unknown space without requiring the additional setup time needed to install new beacons. The performance of the proposed localization system was verified using real experiments.

scholarly journals Indoor Localization Based on Bluetooth

2019 ◽  
Vol 7 (2) ◽  
pp. 87 ◽  
Author(s):  
Jun Yin ◽  
Fengchun Yin
Keyword(s):  
Indoor Localization ◽  
Mobile Terminal ◽  
Indoor Positioning ◽  
Detection Algorithm ◽  
Indoor Environments ◽  
Construction Time ◽  
Indoor Scenes ◽  
Fingerprint Database ◽  
To Receive ◽  
Transmission Speed

Global positioning system (GPS) has been widely used in positioning, vehicle navigation and other environments. However, in indoor environments, it can not achieve accurate positioning because of the weak signal through the wall. In other words, more appropriate techniques are needed in indoor scenes. Bluetooth technology has attracted more and more attention due to its advantages of low power consumption, wide coverage and fast transmission speed. Bluetooth-based indoor positioning refers to the indoor positioning technology that uses mobile terminal to receive Bluetooth signals from multiple Bluetooth devices, and calculates the location information of mobile terminal through the received information, so as to achieve high-precision positioning.In this paper, an effective optimal location algorithm is proposed. Firstly, the outlier detection algorithm is improved to remove the interference of abnormal data on the positioning accuracy; then, different filtering algorithms are used to process the received fingerprint information to ensure the accuracy of the fingerprint database establishment stage, and reduce the unnecessary construction time; finally, the average position is calculated by the average fingerprint data and judged the user's area.

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

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3431
Author(s):  
Mateusz Groth ◽  
Krzysztof Nyka ◽  
Lukasz Kulas
Keyword(s):  
Indoor Environment ◽  
Indoor Localization ◽  
Low Cost ◽  
Indoor Environments ◽  
Calibration Free ◽  
Architecture And Design ◽  
Positioning Algorithm ◽  
Parasitic Array ◽  
Better Than ◽  
Localization Systems

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.

scholarly journals An Efficient Indoor Positioning Method Based on Wi-Fi RSS Fingerprint and Classification Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3418
Author(s):  
Balaji Ezhumalai ◽  
Moonbae Song ◽  
Kwangjin Park
Keyword(s):  
Low Cost ◽  
Clustering Algorithms ◽  
Access Point ◽  
Indoor Positioning ◽  
Reference Points ◽  
Indoor Environments ◽  
Positioning Accuracy ◽  
Signal Distribution ◽  
Positioning Method ◽  
Handling Method

Wi-Fi received signal strength (RSS) fingerprint-based indoor positioning has been widely used because of its low cost and universality advantages. However, the Wi-Fi RSS is greatly affected by multipath interference in indoor environments, which can cause significant errors in RSS observations. Many methods have been proposed to overcome this issue, including the average method and the error handling method, but these existing methods do not consider the ever-changing dynamics of RSS in indoor environments. In addition, traditional RSS-based clustering algorithms have been proposed in the literature, but they make clusters without considering the nonlinear similarity between reference points (RPs) and the signal distribution in ever-changing indoor environments. Therefore, to improve the positioning accuracy, this paper presents an improved RSS measurement technique (IRSSMT) to minimize the error of RSS observation by using the number of selected RSS and its median values, and the strongest access point (SAP) information-based clustering technique, which groups the RPs using their SAP similarity. The performance of this proposed method is tested by experiments conducted in two different experimental environments. The results reveal that our proposed method can greatly outperform the existing algorithms and improve the positioning accuracy by 89.06% and 67.48%, respectively.

scholarly journals Using Acoustic Signal and Image to Achieve Accurate Indoor Localization

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2566 ◽  
Author(s):  
Rui Xi ◽  
Daibo Liu ◽  
Mengshu Hou ◽  
Yujun Li ◽  
Jun Li
Keyword(s):  
Pervasive Computing ◽  
Indoor Localization ◽  
Practical Application ◽  
Location Based Service ◽  
Localization Accuracy ◽  
Indoor Location ◽  
Location Service ◽  
Localization Scheme ◽  
True Location ◽  
Acoustic Sources

Location information plays a key role in pervasive computing and application, especially indoor location-based service, even though a mass of systems have been proposed, an accurate and practical indoor localization system remains unsettled. To tackle this issue, in this paper, we present a new localization scheme, SITE, combining acoustic Signals and Images to achieve accurate and robust indoor locaTion sErvice. Relying on a pre-deployed platform of acoustic sources with different frequencies, using proactively generated Doppler effect signals, SITE could track relative directions between the phone and the sources. Given m (m≥5) relative directions, SITE can use the angle differences to compute a set of locations corresponding to different subsets of sources. Then, based on a key observation—while the simultaneously estimated locations using different sets of acoustic anchors are within a small circle, the results converge to a point near the true location—SITE proposes a decision scheme that confirms whether these locations satisfy the demand of localization accuracy and can be used to search the user’s location. If not, SITE utilizes VSFM(Visual Structure from Motion) technique to achieve a set of relative locations using some images captured by the phone’s camera. By exploiting the synergy between the set of relative locations and the set of initial locations computed by relative directions, an optimal transformation relationship is obtained and applied to refine the initial calculated results. The refined result will be regarded as the user’s location. In the evaluation, we implemented a prototype and deployed a real platform of acoustic sources in different scenarios. Experimental results show that SITE has excellent performance of localization accuracy, robustness and feasibility in practical application.

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