A new method for improving Wi-Fi-based indoor positioning accuracy (original) (raw)
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An Enhanced Indoor Positioning Method Based on Wi-Fi RSS Fingerprinting
JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS, 2019
In WiFi-based indoor positioning, the received signal strength (RSS) measurements are commonly used to estimate the mobile user location. However, these measurements significantly fluctuate over time and are susceptible to human movement, multipath and Non-Line-of-Sight (NLOS) propagation, which reduce the location accuracy. In this paper, an enhanced positioning method based on the nearest neighbor algorithm is proposed. The set of the RSS samples recorded from several Access Points (APs) is used rather than their average, for reducing the location errors introduced by the RSS variations and the multipath problem. The proposed algorithm, named the Nearest K th Nearest Neighbor (NK-NN) is experimentally evaluated and compared to other powerful methods. The results show that the proposed method outperforms these methods.
Indoor Positioning based on Wi-Fi Fingerprint Technique using Fuzzy K-Nearest Neighbor
Indoor positioning system based on Receive Signal Strength Indication(RSSI) from Wireless access equipment have become very popular in recent years. This system is very useful in many applications such as tracking service for older people, mobile robot localization and so on. While Outdoor environment using Global Navigation Satellite System(GNSS) and cellular network works well and widespread for navigator. However, there was a problem with signal propagation from satellites. They cannot be used effectively inside the building areas until a urban environment. In this paper we propose the Wi-Fi Fingerprint Technique using Fuzzy set theory to adaptive Basic K-Nearest Neighbor algorithm to classify the labels of a database system. It was able to improve the accuracy and robustness. The performance of our simple algorithm is evaluated by the experimental results which show that our proposed scheme can achieve a certain level of positioning system accuracy.
Indoor Positioning Using the Modified Fingerprint Technique
2013
The Wi-Fi positioning systems available for enclosed spaces use the existing network infrastructure to calculate the position of the mobile device (MD). The most commonly used parameter is RSSI (Received Signal Strength Indicator). In this paper, we analyze the Fingerprint technique considering some variations aimed at improving the accuracy of the technique and minimizing calculation time. Significant field work is carried out, analyzing the accuracy achieved with each technique.
Using of GSM and Wi-Fi Signals for Indoor Positioning Based on Fingerprinting Algorithms
Advances in Electrical and Electronic Engineering, 2015
In the paper framework for indoor positioning utilizing Wi-Fi and GSM signals is introduced. Nowadays, indoor positioning is a very attractive topic for researchers, since accurate and reliable positioning system can unlock new market to service providers. In this paper we will analyse the use of Wi-Fi and GSM signals and their combination for the fingerprinting based positioning in the indoor environment. Performance of positioning system in terms of accuracy was analysed using simulations. In the simulations the position of the mobile device was estimated in three ways, when only GSM signals were used, when only Wi-Fi signals were utilized and when a combination of both signals was used. Three positioning algorithms from the Nearest Neighbour (NN) family were used in the simulations. Simulations were performed in the simulation model created in MATLAB environment.
Indoor Location Estimation Utilizing Wi-Fi Signals
International Journal of Emerging Trends in Engineering Research, 2020
Global Positioning System is commonly been used for locating a position of a specific structure in finding geographical coordinates of a target area. Though, this application is still having a restricted in term of the signals, might not well operated and ineffective for indoor usage. The study aim is to develop positioning and localization systems by using Wi-Fi signal. Estimation was made based on the measurement of wireless distance for estimation the user's coordinates. Analysis of views called the fingerprint algorithm is used in this study. The algorithm involved two phases over an offline and the online phases of the survey. Unidentified user's coordinates will be in the online phase by comparative databases collected in the survey phase. MATLAB Graphical User Interface and Android has been used to develop a user interface for simulation purposes. Several analyses were performed to define the precision and efficiency of occurred error as the number of access points and the traffic environment. Finally, the user required to provide several inputs e.g. the exact location and the RSS from AP's number at the present location. The simulation-based software will evaluate the estimation location and positioning of the user and will match to user's precise location.
2007
WLAN indoor location that is based on received signal strength indication (RSSI) technique needs extensive calibration to build a signal fingerprint. Re-calibration is also needed if there is a major change in the propagation environment. The use of propagation models to predict signal fingerprint becomes an interesting preposition. This paper will investigate the influence of predicted fingerprint on the accuracy of indoor location. They include empirical propagation models (i.e. one-slope model and multi-wall model) and a semi-deterministic model. A framework for indoor location with the nearest-neighbour and particle filter are developed to evaluate predicted and measured fingerprints. In order to take advantage of environment description, a map-filtering technique is also elaborated.
On the efficacy of WiFi indoor positioning in a practical setting
2013 IEEE Symposium on Computers and Communications (ISCC), 2013
We implement two popular WiFi, fingerprinting based indoor tracking mechanisms, namely the k-nearest neighbours and probabilistic positioning methods. Both mechanisms are evaluated in the context of an indoor position-tracking tablet application, following an investigation to determine optimal working parameters. Our results indicate that even after significant optimisation, both fingerprinting algorithms are highly sensitive to the location of the access points and do not produce finely grained location results. Although in this case the results are accurate enough for our purposes, factors such as the effect of natural body obstruction of the user as well as the location of the access points used in fingerprinting must be considered carefully if more accuracy is required.
Sensors, 2021
Indoor positioning has become a very promising research topic due to the growing demand for accurate node location information for indoor environments. Nonetheless, current positioning algorithms typically present the issue of inaccurate positioning due to communication noise and interferences. In addition, most of the indoor positioning techniques require additional hardware equipment and complex algorithms to achieve high positioning accuracy. This leads to higher energy consumption and communication cost. Therefore, this paper proposes an enhanced indoor positioning technique based on a novel received signal strength indication (RSSI) distance prediction and correction model to improve the positioning accuracy of target nodes in indoor environments, with contributions including a new distance correction formula based on RSSI log-distance model, a correction factor (Beta) with a correction exponent (Sigma) for each distance between unknown node and beacon (anchor nodes) which are ...
Accurate indoor positioning system based on modify nearest point technique
International Journal of Electrical and Computer Engineering (IJECE), 2022
Wireless fidelity (Wi-Fi) is common technology for indoor environments that use to estimate required distances, to be used for indoor localization. Due to multiple source of noise and interference with other signal, the receive signal strength (RSS) measurements unstable. The impression about targets environments should be available to estimate accurate targets location. The Wi-Fi fingerprint technique is widely implemented to build database matching with real data, but the challenges are the way of collect accurate data to be the reference and the impact of different environments on signals measurements. In this paper, optimum system proposed based on modify nearest point (MNP). To implement the proposal, 78 points measured to be the reference points recorded in each environment around the targets. Also, the case study building is separated to 7 areas, where the segmentation of environments leads to ability of dynamic parameters assignments. Moreover, database based on optimum data collected at each time using 63 samples in each point and the average will be final measurements. Then, the nearest point into specific environment has been determined by compared with at least four points. The results show that the errors of indoor localization were less than (0.102 m).
Finding indoor position of person using wi-fi & smartphone:A survey
Positioning system can be used for different purposes and for different services, so a lot of research is going on to find a more accurate position with low error techniques with good results. The Positioning techniques have been actively studied recently due to service as well as safety and security matters. Global Positioning System (GPS) is more widely used for outdoor but GPS is not suitable for indoor . There are many localization systems with different architectures, configurations, accuracies and reliabilities Wi-Fi Positioning system (WPS) solves this problem. Here we find out position with the help of Wi-Fi signal strength. We also discuss location fingerprinting in detail since it is used in most current system or solutions. A small program installed on to calculate the position. This will help in many applications for mobile users and network administrators. It will make use of existing Wi-Fi infrastructure, although Wi-Fi system was never designed to find out the location. The smart device regularly scans the signal strengths for surrounding Wi-Fi access points and send information to a central server. This paper try to survey the recent work related to indoor positioning system.