scholarly journals An Efficient Indoor Wi-Fi Positioning Method Using Virtual Location of AP

2020 ◽  
Vol 9 (4) ◽  
pp. 261
Author(s):  
Fan Xu ◽  
Xuke Hu ◽  
Shuaiwei Luo ◽  
Jianga Shang
Keyword(s):  
Indoor Localization ◽  
Attenuation Factor ◽  
Access Point ◽  
Location Estimation ◽  
Signal Attenuation ◽  
Distance Ratio ◽  
Localization Accuracy ◽  
Access Points ◽  
Attenuation Parameter ◽  
The Impact

Wi-Fi fingerprinting has been widely used for indoor localization because of its good cost-effectiveness. However, it suffers from relatively low localization accuracy and robustness owing to the signal fluctuations. Virtual Access Points (VAP) can effectively reduce the impact of signal fluctuation problem in Wi-Fi fingerprinting. Current techniques normally use the Log-Normal Shadowing Model to estimate the virtual location of the access point. This would lead to inaccurate location estimation due to the signal attenuation factor in the model, which is difficult to be determined. To overcome this challenge, in this study, we propose a novel approach to calculating the virtual location of the access points by using the Apollonius Circle theory, specifically the distance ratio, which can eliminate the attenuation parameter term in the original model. This is based on the assumption that neighboring locations share the same attenuation parameter corresponding to the signal attenuation caused by obstacles. We evaluated the proposed method in a laboratory building with three different kinds of scenes and 1194 test points in total. The experimental results show that the proposed approach can improve the accuracy and robustness of the Wi-Fi fingerprinting techniques and achieve state-of-art performance.

scholarly journals DeepLocate: Smartphone Based Indoor Localization with a Deep Neural Network Ensemble Classifier

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 133 ◽  
Author(s):  
Imran Ashraf ◽  
Soojung Hur ◽  
Sangjoon Park ◽  
Yongwan Park
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Indoor Localization ◽  
Ensemble Classifier ◽  
Location Based Services ◽  
Magnetic Data ◽  
Neural Network Ensemble ◽  
Localization Accuracy ◽  
Mean Error ◽  
The Impact

A quickly growing location-based services area has led to increased demand for indoor positioning and localization. Undoubtedly, Wi-Fi fingerprint-based localization is one of the promising indoor localization techniques, yet the variation of received signal strength is a major problem for accurate localization. Magnetic field-based localization has emerged as a new player and proved a potential indoor localization technology. However, one of its major limitations is degradation in localization accuracy when various smartphones are used. The localization performance is different from various smartphones even with the same localization technique. This research leverages the use of a deep neural network-based ensemble classifier to perform indoor localization with heterogeneous devices. The chief aim is to devise an approach that can achieve a similar localization accuracy using various smartphones. Features extracted from magnetic data of Galaxy S8 are fed into neural networks (NNs) for training. The experiments are performed with Galaxy S8, LG G6, LG G7, and Galaxy A8 smartphones to investigate the impact of device dependence on localization accuracy. Results demonstrate that NNs can play a significant role in mitigating the impact of device heterogeneity and increasing indoor localization accuracy. The proposed approach is able to achieve a localization accuracy of 2.64 m at 50% on four different devices. The mean error is 2.23 m, 2.52 m, 2.59 m, and 2.78 m for Galaxy S8, LG G6, LG G7, and Galaxy A8, respectively. Experiments on a publicly available magnetic dataset of Sony Xperia M2 using the proposed approach show a mean error of 2.84 m with a standard deviation of 2.24 m, while the error at 50% is 2.33 m. Furthermore, the impact of devices on various attitudes on the localization accuracy is investigated.

scholarly journals Fusion of Channel State Information and Received Signal Strength for Indoor Localization Using a Single Access Point

2020 ◽  
Vol 12 (12) ◽  
pp. 1995
Author(s):  
David Sánchez-Rodríguez ◽  
Miguel A. Quintana-Suárez ◽  
Itziar Alonso-González ◽  
Carlos Ley-Bosch ◽  
Javier J. Sánchez-Medina
Keyword(s):  
Channel State Information ◽  
Indoor Localization ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Channel State ◽  
State Information ◽  
Single Access ◽  
5 Ghz

In recent years, indoor localization systems based on fingerprinting have had significant advances yielding high accuracies. Those approaches often use information about channel communication, such as channel state information (CSI) and received signal strength (RSS). Nevertheless, these features have always been employed separately. Although CSI provides more fine-grained physical layer information than RSS, in this manuscript, a methodology for indoor localization fusing both features from a single access point is proposed to provide a better accuracy. In addition, CSI amplitude information is processed to remove high variability information that can negatively influence location estimation. The methodology was implemented and validated in two scenarios using a single access point located in two different positions and configured in 2.4 and 5 GHz frequency bands. The experiments show that the methodology yields an average error distance of about 0.1 m using the 5 GHz band and a single access point.

scholarly journals SICD: Novel Single-Access-Point Indoor Localization Based on CSI-MIMO with Dimensionality Reduction

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1325
Author(s):  
Yunwei Zhang ◽  
Weigang Wang ◽  
Chendong Xu ◽  
Jie Qin ◽  
Shujuan Yu ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Indoor Localization ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Location Based Services ◽  
Localization Accuracy ◽  
Single Access ◽  
Time Frequency ◽  
High Data ◽  
Log Normal

With the rise of location-based services and the rapidly growing requirements related to their applications, indoor localization based on channel state information–multiple-input multiple-output (CSI-MIMO) has become an important research topic. However, indoor localization based on CSI-MIMO has some disadvantages, including noise and high data dimensions. To overcome the above drawbacks, we proposed a novel method of indoor localization based on CSI-MIMO, named SICD. For SICD, a novel localization fingerprint was first designed which can reflect the time–frequency and space–frequency characteristics of CSI-MIMO under a single access point (AP). To reduce the redundancy in the data of CSI-MIMO amplitude, we developed a data dimensionality reduction algorithm. Moreover, by leveraging a log-normal distribution, we calculated the conditional probability of the naive Bayes classifier, which was used to predict the moving object’s location. Compared with other state-of-the-art methods, the results of the experiment confirm that the SICD effectively improves localization accuracy.

scholarly journals A Simple Indoor Localization Methodology for Fast Building Classification Models Based on Fingerprints

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 103 ◽  
Author(s):  
David Sánchez-Rodríguez ◽  
Itziar Alonso-González ◽  
Carlos Ley-Bosch ◽  
Miguel Quintana-Suárez
Keyword(s):  
Indoor Localization ◽  
Estimation Error ◽  
Computational Cost ◽  
Access Point ◽  
Visible Light Communication ◽  
High Energy ◽  
Location Estimation ◽  
Localization System ◽  
Emergency Situations ◽  
Computational Performance

Indoor localization has received tremendous attention in the last two decades due to location-aware services being highly demanded. Wireless networks have been suggested to solve this problem in many research works, and efficient algorithms have been developed with precise location and high accuracy. Nevertheless, those approaches often have high computational and high energy consumption. Hence, in temporary environments, such as emergency situations, where a fast deployment of an indoor localization system is required, those methods are not appropriate. In this manuscript, a methodology for fast building of an indoor localization system is proposed. For that purpose, a reduction of the data dimensionality is achieved by applying data fusion and feature transformation, which allow us to reduce the computational cost of the classifier training phase. In order to validate the methodology, three different datasets were used: two of them are public datasets based mainly on Received Signal Strength (RSS) from different Wi-Fi access point, and the third is a set of RSS values gathered from the LED lamps in a Visible Light Communication (VLC) network. The simulation results show that the proposed methodology considerably amends the overall computational performance and provides an acceptable location estimation error.

scholarly journals Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3282 ◽  
Author(s):  
Umair Mujtaba Qureshi ◽  
Zuneera Umair ◽  
Gerhard Petrus Hancke
Keyword(s):  
Indoor Localization ◽  
Low Energy ◽  
Transmission Power ◽  
Pass Filter ◽  
Bluetooth Low Energy ◽  
Localization Accuracy ◽  
Localization Model ◽  
Localization Precision ◽  
The Impact ◽  
Wireless Indoor Localization

Bluetooth Low Energy (BLE) based Wireless Indoor Localization System (WILS) with high localization accuracy and high localization precision is a key requirement in enabling the Internet of Things (IoT) in today’s applications. In this paper, we investigated the effect of BLE signal variations on indoor localization caused by the change in BLE transmission power levels. This issue is not often discussed as most of the works on localization algorithms use the highest power levels but has important practical implications for energy efficiency, e.g., if a designer would like to trade-off localization performance and node lifetime. To analyze the impact, we used the established trilateration based localization model with two methods i.e., Centroid Approximation (CA) and Minimum Mean Square Error (MMSE). We observed that trilateration based localization with MMSE method outperforms the CA method. We further investigated the use of two filters i.e., Low Pass Filter (LPF) and Kalman Filter (KF) and evaluated their effects in terms of mitigating the random variations from BLE signal. In comparison to non-filter based approach, we observed a great improvement in localization accuracy and localization precision with a filter-based approach. Furthermore, in comparison to LPF based trilateration localization with CA, the performance of a KF based trilateration localization with MMSE is far better. An average of 1 m improvement in localization accuracy and approximately 50% improvement in localization precision is observed by using KF in trilateration based localization model with the MMSE method. In conclusion, with KF in trilateration based localization model with MMSE method effectively eliminates random variations in BLE RSS with multiple transmission power levels and thus results in a BLE based WILS with high accuracy and high precision.

Survey on the Indoor Localization Technique of Wi-Fi Access Points

2018 ◽  
Vol 10 (3) ◽  
pp. 27-42
Author(s):  
Yimin Liu ◽  
Wenyan Liu ◽  
Xiangyang Luo
Keyword(s):  
Indoor Localization ◽  
Signal Strength ◽  
Access Point ◽  
Distance Measurement ◽  
Basic Principles ◽  
Localization Technique ◽  
Related Research ◽  
Research Results ◽  
Access Points ◽  
Fingerprint Feature

This article describes how indoor localization of Wi-Fi AP (access point) plays an important role in the discovery of illegal indoor Wi-Fi and for the safety inspection of confidential places. There have been many related research results in recent years. In this article, a review is presented on the indoor localization technique of Wi-Fi AP. First, indoor localization methods of Wi-Fi AP can be divided into three categories: localization based on signal strength; fingerprint feature; and distance measurement. Then, the basic principles of the three methods are described respectively, and an evaluation of the typical methods are provided. Finally, the authors point out some research tendency of the indoor localization techniques of Wi-Fi AP.

scholarly journals RSS Indoor Localization Based on a Single Access Point

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3711 ◽  
Author(s):  
Akis Kokkinis ◽  
Loizos Kanaris ◽  
Antonio Liotta ◽  
Stavros Stavrou
Keyword(s):  
Nearest Neighbor ◽  
Indoor Localization ◽  
Minimum Mean Square Error ◽  
Research Work ◽  
Access Point ◽  
Probabilistic Algorithms ◽  
K Nearest Neighbor ◽  
Localization Accuracy ◽  
Area Of Interest ◽  
Normal Probability Distribution

This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor—WKNN and Minimum Mean Square Error—MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the “Tolerance Based—Normal Probability Distribution (TBNPD)” algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP.

scholarly journals A Probabilistic Approach for Optimal Design of Indoor Positioning Systems

2020 ◽  
Author(s):  
Bráulio Henrique O. U. V. Pinto ◽  
Horácio A. B. F. de Oliveira ◽  
Eduardo Souto
Keyword(s):  
Indoor Positioning ◽  
Location Estimation ◽  
Reference Points ◽  
Location Based Services ◽  
Design Parameters ◽  
Area Network ◽  
Localization Error ◽  
Positioning Systems ◽  
Access Points ◽  
The Impact

Indoor Positioning Systems (IPSs) are designed to provide solutions for location-based services. Wireless local area network (WLAN)-based positioning systems are the most widespread around the globe and are commonly found to have a ready-to-use infrastructure composed mostly of access points (APs). They provide useful information on signal strength to be processed by adequate location algorithms, which are not always capable of achieving the desired localization error only by themselves. In this sense, this paper proposes a new method to improve the accuracy of IPSs by optimizing some of their most relevant infrastructure components. Included are the arrangement of APs over the environment, the number of reference points (RPs), and the number of samples per location estimation test. A simulation environment is also proposed, in which the impact of key influencing factors on system accuracy is analyzed. Finally, a case study is simulated to validate an optimal combination of design parameters and its compliance with the requirements of localization error and the limited number of access points. Our simulation results clearly show that the desired localization accuracy, which is set as a goal, can be achieved while maintaining the factors already mentioned at minimal levels, which decreases both system deployment costs and computational effort.

scholarly journals Analysis of EMC problems with the purpose of developing an effective method of WLAN design on the basis of information systems considering electromagnetic

Connectivity ◽  
2020 ◽  
Vol 146 (5) ◽  
Author(s):  
A. V. Lemeshko ◽  
◽  
O. M. Tkachenko ◽  
А. О. Makarenko ◽  
O. M. Tkalenko ◽  
...  
Keyword(s):  
Information Systems ◽  
Electromagnetic Interference ◽  
Local Area Networks ◽  
Access Point ◽  
Local Area ◽  
Wireless Local Area Networks ◽  
Ieee 802.11E ◽  
Detection Range ◽  
Access Points ◽  
The Impact

The article analyzes the scope, technologies and principles of wireless local area networks, which allowed to mark the “bottlenecks” of these technologies, which need special attention when designing: the problem of hidden node; mutual interference between neighboring cells (intrasystem EMC); intersystem interference; providing QoS for responsible applications; expansion of wireless local area networks; the impact of network deployment features. The methods used to solve EMC problems in wireless local area networks are shown and their efficiency is analyzed: the mechanism of access to the transmission medium; IEEE 802.11e (QoS) standard; additional standards designed to reduce the impact of interference (802.11 h and k); coding and modulation. It is shown that the accounting of intrasystem and intersystem interference should be carried out in the early stages of design of wireless local area networks. It is shown that the existing mechanisms of access to the transmission medium are designed to organize the conflict-free operation of transceivers within a single access point and are vulnerable to interference created by transmission stations of neighboring access points. The dynamic sensitivity control algorithm is aimed at partially solving this problem, however, the main disadvantage of the DCC algorithm proposed for use in Wi-Fi 6 is that stations located near access points have a higher probability of access to the environment due to a higher signal level. Relative to electromagnetic interference, which leads to a shorter detection range of the carrier. That requires the development of advanced mechanisms to control the sensitivity of the service area of access points. Based on the analysis, a conclusion is made about the need to develop a methodology for designing wireless local area networks based on information systems, taking into account electromagnetic interference. Which will reduce the time of their design and increase the efficiency of their further operation.

scholarly journals A Constrained Kalman Filter for Wi-Fi-Based Indoor Localization with Flexible Space Organization

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 428
Author(s):  
Vincent Sircoulomb ◽  
Houcine Chafouk
Keyword(s):  
Kalman Filter ◽  
Indoor Localization ◽  
Fast Computation ◽  
Localization Accuracy ◽  
Access Points ◽  
Space Organization

This paper presents a constrained Kalman filter for Wi-Fi-based indoor localization. The contribution of this work is to introduce constraints on the object speed and to provide a numerically optimized form for fast computation. The proposed approach is suitable to flexible space organization, as in warehouses, and when objects can be spun around, for example barcode readers in a hand. We experimented with the proposed technique using a robot and three devices, on five different journeys, in a 6000 m2 warehouse equipped with six Wi-Fi access points. The results highlight that the proposed approach provides a 19% improvement in localization accuracy.

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