Jozef Benikovsky

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.

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.

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.

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.

Localization in Real GSM Network with Fingerprinting Utilization

This paper attempts to present current state in the area of user localization in cellular networks and shows custom solution for positioning using pocket computer and fingerprint method also known as fingerprinting. It operates in Global System for Mobile communications (GSM) network, although fingerprinting is also applicable in other wireless networks, such as Universal Mobile Telecommunications System (UMTS), Bluetooth or 802.11. Implementation is explained and it is compared to existing solutions. The performance of the system is evaluated for various scenarios by statistical characteristics and Circular Error Probability (CEP). The scenarios are proposed from observation of various parameters that influence the localization accuracy.

Optimization of the RBF localization algorithm using Kalman filter

In this paper an optimization of the Rank Based Fingerprinting (RBF) algorithm using the Kalman filter will be introduced. In our previous papers it was shown that RBF localization algorithm seems to be more immune and accurate compared to traditional deterministic fingerprinting algorithms. We still decided to improve accuracy of the algorithm in dynamic applications, like navigation or user tracking. For this purpose Kalman filter was implemented to the previously developed localization system. Impact of the proposed solution on the accuracy and functionality of the RBF localization algorithm was investigated in the simulations and verified real world experiments. Simulations were performed in model created in Matlab environment. Real world measurements were performed at the campus of the University of Zilina using WifiLOC localization system developed at the Department of Telecommunications and Multimedia.

Scalability Optimization of Seamless Positioning Service

Recently positioning services are getting more attention not only within research community but also from service providers. From the service providers point of view positioning service that will be able to work seamlessly in all environments, for example, indoor, dense urban, and rural, has a huge potential to open new markets. However, such system does not only need to provide accurate position estimates but have to be scalable and resistant to fake positioning requests. In the previous works we have proposed a modular system, which is able to provide seamless positioning in various environments. The system automatically selects optimal positioning module based on available radio signals. The system currently consists of three positioning modules—GPS, GSM based positioning, and Wi-Fi based positioning. In this paper we will propose algorithm which will reduce time needed for position estimation and thus allow higher scalability of the modular system and thus allow providing positioning services to higher amount of users. Such improvement is extremely important, for real world application where large number of users will require position estimates, since positioning error is affected by response time of the positioning server.

Impact of APs removal on accuracy of fingerprinting localization algorithms

In this paper the impact of the Access Points (APs) removal on localization accuracy of Rank Based Fingerprinting (RBF) will be investigated using simulations. The RBF algorithm was previously proposed by the authors and it seems to improve performance of the traditional fingerprinting algorithms and reduce impact of the device change on the accuracy of the positioning process. In the first part of the paper the impact of APs with different Received Signal Strength values on the performance of the positioning using RBF algorithm will be investigated. Based on results achieved in the simulation, algorithm for APs removal will be proposed and tested in simulations and real world experiments. Simulations will be performed in the model created in Matlab environment. Results achieved by the RBF algorithm during will be compared to the results achieved by the traditional Nearest Neighbour family algorithms.

A study on the accuracy of AGA positioning algorithm in multipath environment

The quality of location-based services (LBS) services depends on the available accuracy of the used positioning method. There are generally several ones for wireless networks. The more accurate methods are way more expensive to implement. On the contrary, there are methods with lower accuracy and much lower costs as well. Received signal strength (RSS) method, which is described below, belongs to the latter case. The purpose of this paper is to describe a performance of adaptive geometric algorithm (AGA) for estimation of mobile station position in multipath environment. The algorithm is an improved version of basic geometric algorithm and it is compared to it as well as to Standard Least Squares method. The properties of the proposed algorithm are evaluated in a simulation and experimental scenario. Both scenarios are implemented in typical multipath conditions, which are crucial in wireless communication.