Myungin Ji

Analysis of positioning accuracy corresponding to the number of BLE beacons in indoor positioning system

In these days, a technology that utilize of Bluetooth Low Energy (BLE) beacon, has been attracted attention to provide variety of convenience services. Especially, not limited to the service that can assist to people directly such as public safety, healthcare, proximity-based service, mobile payment, etc., a technology that can provide convenience indirectly such as asset tracking has also been proposed. Most of all, the indoor location awareness using BLE beacon is the essential technique that can realize these services, it is expected to be more focused if the more BLE beacon is spread in the future. In this paper, we first analyse practical path loss model of BLE signals with compared to that of Wi-Fi signals in order to take advantage of the BLE beacon for indoor positioning. To estimate the practical path loss model, we employed four BLE beacons (each two beacon is the same manufacturer) and two of Wi-Fi AP. Each signal was measured during one minute at each reference distance from lm to 13m (with 2m interval) in a Line-of-Sight (LOS) environment. The calculated path loss model was used to generate a BLE signal virtually, we applied the model to configure the BLE radiomap and generate positioning measurement data in our simulation. Since BLE signal has relatively lower tx power compared to Wi-Fi APs, it requires much more beacons to achieve comparable positioning accuracy. We focused on the relationship between the number of installed beacon and its positioning accuracy in this paper.

WiFi AP position estimation using contribution from heterogeneous mobile devices

We analyze a statistical characteristics of WiFi RSSI difference from heterogeneous devices and propose its normal distributed model for cancelling the effect of the diversity of devices on WiFi APs RSSI measurements. To evaluate the accuracy enhancement of WiFi AP position through WiFi RSSI difference correction, four devices with different WiFi chipsets are used to collect measurements in a small-scale testbed. As a result, the correction can normalize WiFi RSSI measurements from heterogeneous devices into WiFi RSSI measurements from a reference device so that the quick and accurate survey is achievable by using multiple devices in wide indoor area. Furthermore, user generated contribution, which uses heterogeneous devices, can be easily applied to the WiFi AP position estimation by using this correction.

A novel Wi-Fi AP localization method using Monte Carlo path-loss model fitting simulation

Wi-Fi-based localization is one of the most promising technologies for indoor location-based services. However, it is still a difficult task to construct a positioning database to provide high accuracy and vast coverage, especially in probabilistic-based algorithms such as fingerprint-based localization. On the other hand, positioning methods that use the location database of the positioning infrastructure, such as the weighted centroid method, can support terminal-based localization due to lower computational complexity and small database size. Terminal-based positioning has the advantages not only of protecting personal location information, but also of maintaining the network topology among the terminals. The only weak point for positioning database-based methods is that the accurate location of the infrastructure should be known in advance. In this paper, we propose a novel algorithm to estimate the location of infrastructure, especially for Wi-Fi access points. We developed and employed a smartphone application to collect Wi-Fi signals by just walking around the test area. Then, the locations of Wi-Fi access points are estimated efficiently and accurately by selection of the maximum likelihood position that has the most similar path-loss model corresponding to the signal acquisition points. The estimated locations are processed as infrastructure database to support terminal-based positioning. The simulation and experiment result validate the feasibility of the proposed algorithm. The estimated location of access points is within 10 m accuracy in most cases and also the terminal-based positioning results achieve competitive performance comparing with other positioning methods.

Fingerprint DB generating system exploiting PDR based dynamic collection for indoor localization of smart-phone users

The fingerprinting has been considered as a promising method for indoor localization due to the robustness from the multi-path than other methods exploiting wireless signals. However, the fingerprinting method has serious limitation which it requires too much time and cost to construct a DB (Data Base) before positioning. In conventional static collection based fingerprint DB generation system, it usually takes up to several minutes to obtain a radio pattern for a single reference point comprising very small part of whole service areas. To overcome the drawback, the fingerprint DB generation system based on the dynamic collection, which breaks the tradition of the radio pattern collection, is proposed. In contrast to the conventional collection method, a collector carrying a smart-phone moves pre-designated routes in service areas, and the position and the radio patterns are autonomously gathered by the collecting application in the smart-phone at every seconds. With the dynamically collected data, then, the fingerprint DB is finally generated by averaging method. From the experimental results, it is validated that the proposed collection method remarkably improves the efficiency of the collection. Also, the positioning using the generated DB shows reasonable accuracy, 2.62m, in an indoor office environment.

A Novel Multi-channel Multi-radio Wireless Mesh Node Architecture for NS-2

In this paper, we propose new network simulator architecture to simulate the performance of multi-channel multi-radio mesh network in the NS-2. We add Multi-radio abstraction layer to manage multiple radio instances, and we are able to simulate regardless of the number of channels and radios in each node. Most of all, we implement some important procedures for realistic multi-channel multi-radio experiments such as channel switching mechanism and multiple radio usage policy. Using this architecture, we evaluate the performance when all of nodes utilize 3 radios according to the number of available channels. Simulation results show that the performance can be improved up to 2.15 times compared to using 2 radios.

High-scalable 3D indoor positioning algorithm using loosely-coupled Wi-Fi/sensor integration

This paper proposes high-scalable 3D indoor positioning algorithm in commercial smart-phone by combining two complementary technologies, Wi-Fi and sensor based positioning. Because a smartphone usually has low-grade MEMS sensor and heterogeneous Wi-Fi chipset, its very difficult to achieve the globally bounded position in scalable indoor environment. Furthermore, the deployment of wireless infrastructure, e.g. Wi-Fi, is hardly controlled by LBS service providers due to the gigantic set-up cost and time. Considering this limitation, the proposed solution is most realistic and opportunistic positioning method, in especially large and complex indoor environment. Firstly, our indoor LBS platform is summarized for understanding the high-level architecture. Then the principle and concept of this proposed algorithm is described. Finally, the experimental set-up and its results are analysed and its successful achievement are presented from about half an hour test scenario.

K-NN based positioning performance estimation for fingerprinting localization

The positioning system have been paid lots of attention to deal with numerous demands of providing location based services to users. To develop a positioning system, a target accuracy should be defined for reliable services. Though a same system is applied, however, the positioning performance is not always identical since signal environments and structure of indoor areas are different. If a system cannot achieve the target accuracy, the system and environments should be re-examined to find out a solution to meet the accuracy. As a result, additional costs are required to establish a positioning system soundly operable in broad areas. To reduce the cost, in this paper, a system for positioning performance estimation is addressed, especially for fingerprinting positioning system. The proposed system measures signal distances between location fingerprints constituting a radio-map to evaluate the similarity between the signal patterns. Ambiguous patterns bring larger positioning errors when signal fluctuations are introduced; therefore, by calculating the similarity the performance it gives an evidence to estimate degree of positioning errors. The experimental results in subway stations in Seoul, Korea, verify the feasibility of the proposed system.

Design of positioning DB automatic update method using Google tango tablet for image based localization system

Recent, many people are working in the indoor space and a large and complex buildings are being increased. And indoor location-based service is required based on the exact position of the user, a variety of indoor positioning technologies have been researched. In this paper, we propose a design for positioning DB updating method for the image based positioning system using Google project tango device.

Performance evaluation of fingerprint based location system using dynamic collection

The fingerprinting location system has been considered as a possible solution for indoor localization. However, it has a problem for building radiomaps for broad areas due to the laborious site-surveying process. A dynamic collection based radiomap generation system is proposed in the literature for solving the problem. With the same dynamically collected measurements, however, the positioning performance may vary significantly. In this paper, therefore, the performances of the fingerprinting location system which exploits dynamic collection are evaluated in various environments. The experimental results verify that the positioning performances are affected by some parameters, so they should be thoroughly decided.

GPR based Wi-Fi radio map construction from real/virtual indoor dynamic surveying data

The scalable and cost-effective Wi-Fi radio-map construction is very important to revitalize indoor location-based service. Considering indoor dynamic surveying data for this purpose, the noble radio map construction method is necessary. With the limitation of indoor dynamic surveying, that is, only access to public area and sensitive signal strength reception, the GPR (Gaussian Process Regression) based radio-map construction method exploiting both realistic and virtual indoor dynamic surveying data is proposed and evaluated. The virtual indoor dynamic surveying data consists of a set of locations and its RSSI where the realistic surveying data is rare, by using access points signal propagation model. The results show that this method can obtain not only high accuracy but also high availability in the whole indoor service area even though the realistic indoor surveying data is rare and its distribution is lack of uniformity.