On the Move Passive Localization of Access Points Based on Received Signal Strength of IEEE 802.11 Probe Frames: A Heuristic Method

Author(s):  
Kaushik Ghosh ◽  
Ajay Prasad
Author(s):  
Carlos Fco Álvarez Salgado ◽  
Luis E. Palafox Maestre ◽  
Leocundo Aguilar Noriega ◽  
Juan R. Castro

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986613 ◽  
Author(s):  
Dong Myung Lee ◽  
Boney Labinghisa

In indoor positioning techniques, Wi-Fi is one of the most used technology because of its availability and cost-effectiveness. Access points are usually the main source of Wi-Fi signals in an indoor environment. If access points are optimized to cover the indoor area, this could improve Wi-Fi signal distribution. This article proposed an alternative to optimizing access point placement and distribution by introducing virtual access points that can be virtually placed in any part of the indoor environment without installation of actual access points. Virtual access points will be created heuristically by correlating received signal strength indicator of already existing access points and through linear regression. After introducing virtual access points in the indoor environment, next will be the addition of filters to improve signal fluctuation and reduce noise interference. Kalman filter has been previously used together with virtual access point and showed improvement by decreasing error distance of Wi-Fi fingerprinting results. This article also aims to include particle filter in the system to further improve localization and test its effectiveness when paired with Kalman filter. The performance testing of the algorithm in different indoor environments resulted in 3.18 and 3.59 m error distances. An improvement was added on the system by using relative distances instead of received signal strength indicator values in distance estimation and gave an error distance average of 1.85 m.


Author(s):  
Ahmad Abadleh

This paper presents an approach to automatically detect the position of the Wi-Fi access points. It uses Wi-Fi received signal strength as well as some characteristics of the buildings such as the height of the building and the movement direction of the user to detect the position of the access points. This approach comprised of two phases: in phase one, a dynamic threshold is computed for each detected access point using the highest received signal strength. Then the threshold is used to detect a small area surrounding the access point. In phase two, it detects the position of the access point by monitoring the angle between the user and the access point, if the angle is in a certain range, then the position of the access point is detected. The experiments results show a high accuracy achieved by the proposed approach. Moreover, the results show that the proposed approach is promising.


2019 ◽  
Vol 15 (5) ◽  
pp. 155014771985203
Author(s):  
Wenyan Liu ◽  
Xiangyang Luo ◽  
Qing Mu ◽  
Yimin Liu ◽  
Fenlin Liu

The localization accuracy of the existing methods for indoor Wi-Fi access points ranging-based localization depends on the accuracy of the received signal strength measured. Because the existing ranging-based methods are interfered by various indoor environmental factors, it is difficult to accurately measure the received signal strength, which leads to the problem of low localization accuracy of the indoor Wi-Fi access points. An indoor Wi-Fi access points localization algorithm based on improved path loss model parameter calculation method and recursive partition is proposed in this article. The algorithm recursively partitions the region where the target Wi-Fi access points are located according to the idea of quadtree partition, and partitions it into same sub-grids, which is sequentially performed until the sub-grids are smaller than the set threshold. The detection device is used at the detection location of the grids to measure the received signal strength, which is from the detection points to the target access point, the grid center point is used as the location of the candidate target access point, the parameters in the path loss model are calculated by using the signal strength differences between the detection points, and then the distances between the detection points and the target access point are calculated by using the signal strength values from the detection points to the target access point. Finally, the location of the target access point is estimated by executing a localization algorithm, and the location of the grid center point closest to the target access point is taken as the location of the target access point. The experimental results show that under the premise that the target access point can be found, the proposed algorithm reduces the use of the device and improves the localization accuracy compared with the typical localization method.


2021 ◽  
Vol 11 (1) ◽  
pp. 13-20
Author(s):  
Roman Y. Korolkov ◽  
Serhii V. Kutsak

The “Evil twin” rogue access point is one of the most serious security threats to wireless LANs. To solve this problem, a practical approach has been proposed for detecting rogue access points using the received signal strength indicator (RSSI). First, a distributed architecture is presented, which consists of three network analyzers. Then, a cluster analysis of the RSSI vectors is performed to determine the attack. The coordinates of the centroids of clusters obtained were converted into the distance by using an empirical model of signal propagation under indoor conditions. The obtained distances are used to determine the localization of a rogue access point (RAP) using the trilateration method. Finally, we are conducting experiments to evaluate the performance of practical RAP detection. The results show that the proposed approach to detecting rogue access points can significantly reduce the frequency of false alarms, while providing an average localization error of 1.5m, which is quite acceptable for RAP localization in real indoor conditions.


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