Juraj Machaj

Rank based fingerprinting algorithm for indoor positioning

A novel Received Signal Strength (RSS) rank based fingerprinting algorithm for indoor positioning is presented. Because RSS rank is invariant to bias and scaling, the algorithm provides the same accuracy for any receiver device, without the need for RSS calibration. Similarity measures to compare ranked vectors are introduced and their impact on positioning accuracy is investigated in experiments. Experimental results shown that proposed algorithm can achieve better accuracy than commonly used NN and WKNN fingerprinting algorithms.

Proposal of user adaptive modular localization system for ubiquitous positioning

The paper deals with general concept of modular and portable localization system that utilizes existing radio network infrastructure. The modularity means multiple independent collections of algorithms and technologies that allow determining geographical position in various radio and geographical environments. The portability of the system is provided by implementation into small pocket-sized device. The environments are characterized mostly by the parameters of available radio systems such as Global System for Mobile Communications (GSM), Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard-based ones or Global Navigation Satellite Systems (GNSS). Suitable software and utilization of a portable device equipped with necessary hardware can turn the system into the provider of ubiquitous positioning service.

Performance comparison of similarity measurements for database correlation localization method

User positioning is a very important feature in user adaptive system. The user position can be estimated by various positioning methods. This paper investigates an impact of similarity measurements on localization error in deterministic database correlation method. It is also called fingerprinting. Main idea is to compare widely used Euclidean distance with other similarity measurements. Seven different similarity measurements are implemented to simulation model created in Matlab software tool. Computation complexity of each similarity measurement is investigated and impact of similarity measurements on localization error in normal and extreme conditions is shown.

A Novel Enhanced Positioning Trilateration Algorithm Implemented for Medical Implant In-Body Localization

Medical implants based on wireless communication will play crucial role in healthcare systems. Some applications need to know the exact position of each implant. RF positioning seems to be an effective approach for implant localization. The two most common positioning data typically used for RF positioning are received signal strength and time of flight of a radio signal between transmitter and receivers (medical implant and network of reference devices with known position). This leads to positioning methods: received signal strength (RSS) and time of arrival (ToA). Both methods are based on trilateration. Used positioning data are very important, but the positioning algorithm which estimates the implant position is important as well. In this paper, the proposal of novel algorithm for trilateration is presented. The proposed algorithm improves the quality of basic trilateration algorithms with the same quality of measured positioning data. It is called Enhanced Positioning Trilateration Algorithm (EPTA). The proposed algorithm can be divided into two phases. The first phase is focused on the selection of the most suitable sensors for position estimation. The goal of the second one lies in the positioning accuracy improving by adaptive algorithm. Finally, we provide performance analysis of the proposed algorithm by computer simulations.

A modular localization system as a positioning service for road transport.

In recent times smart devices have attracted a large number of users. Since many of these devices allow position estimation using Global Navigation Satellite Systems (GNSS) signals, a large number of location-based applications and services have emerged, especially in transport systems. However GNSS signals are affected by the environment and are not always present, especially in dense urban environment or indoors. In this work firstly a Modular Localization Algorithm is proposed to allow seamless switching between different positioning modules. This helps us develop a positioning system that is able to provide position estimates in both indoor and outdoor environments without any user interaction. Since the proposed system can run as a service on any smart device, it could allow users to navigate not only in outdoor environments, but also indoors, e.g., underground garages, tunnels etc. Secondly we present the proposal of a 2-phase map reduction algorithm which allows one to significantly reduce the complexity of position estimation processes in case that positioning is performed using a fingerprinting framework. The proposed 2-phase map reduction algorithm can also improve the accuracy of the position estimates by filtering out reference points that are far from the mobile device. Both algorithms were implemented into a positioning system and tested in real world conditions in both indoor and outdoor environments.

Optimization of rank based fingerprinting localization algorithm

This paper deals with optimization of the Rank Based Fingerprinting (RBF) algorithm, which was previously proposed by the author. Results achieved in the real world experiments shown that RBF algorithm can achieve more accurate position estimate compared to some of traditional fingerprinting algorithms. Accuracy of the RBF algorithm seems to be less affected by change of device and small signal fluctuations since algorithm is based on assumption that bias and scale of measured RSS data will not affect rank of the APs. Optimization algorithm that significantly reduces computational complexity of the RBF algorithm will be introduced. Function of the algorithm was investigated in the simulations and real world experiments. Achieved results show that proposed optimization algorithm can significantly decrease computation complexity, especially when radio map database is high enough. Achieved results show that proposed optimization algorithm allows use of the RBF algorithm in applications, where the position estimate must be calculated in a very short time e.g. tracking and navigation applications.

Impact of the number of access points in indoor fingerprinting localization

In the paper the solution for indoor positioning based on IEEE 802.11 platform is proposed and experimentally verified. The paper investigates an impact of the number of access points on the localization accuracy in fingerprinting method. The solution is based on deterministic approach. The properties of the solution are tested by experimental measurements in real environment.

A new Complex Angle of Arrival location method for ad hoc networks

Localization is an important and extensively studied problem in wireless ad hoc networks. The process of position discovery can be realized utilizing range measurements including received signal strength, time of arrival or angle of arrival. We focus on localization method based on angle of arrival information between neighbor nodes. This paper proposes an original positioning algorithm to improve positioning accuracy of angle of arrival (AoA) methods. It is called Complex Angle of Arrival (CAoA). Simulations show that CAoA achieves better positioning results compared to conventional AoA method.

Indoor Positioning System Designed for User Adaptive Systems

The paper deals with the indoor positioning solution based on utilization of IEEE 802.11 network and fingerprinting method. This solution was designed as a part of user adaptive integrated positioning system that provides location-based services in indoor environment. The integrated positioning system is engineered for ubiquitous positioning, i.e. anywhere and anytime. The system for indoor environment is called WifiLOC and it is implemented as a mobile-assisted positioning system. The architecture and fundamental principles of the WifiLOC system are presented in this paper. The positioning system is based on the fingerprinting method, which utilizes signal strength information for position estimation.

Performance investigation of WifiLOC positioning system

The paper deals with performance evaluation of the indoor positioning solution based on utilization of IEEE 802.11 network and fingerprinting method. It is called WifiLOC and it is implemented as a mobile-assisted positioning system. The architecture of the system is presented. WifiLOC is based on the fingerprinting method, which utilizes signal strength information for position estimation. A lot of factors influence the propagation of radio signals in indoor environment. This fact also significantly impacts on properties of the positioning systems. In the paper, the impact of the positioning accuracy is presented various conditions such as moving objects in the observed area or the type of indoor environment, e.g. corridor, office and room, are taken into account. The influence of different conditions during the off-line and the on-line phase of fingerprinting method on the positioning accuracy is also investigated.