A Fast Calibration Method for Triaxial-Magnetometers

This paper presents a novel iterative calibration algorithm for tri-axial magnetometers. The proposed algorithm estimates and compensates the effects of deterministic interference parameters using only nine distinct measurements. The simulation results confirm that the proposed method outperforms the conventional ellipsoid fitting based models in terms of both accuracy and reliability even with the presence of a moderate wideband noise. The algorithm also achieves fast convergence , which makes it suitable for real-time application

A Survey on Smartphone-based Systems for Opportunistic User Context Recognition

The ever-growing computation and storage capability of mobile phones have given rise to mobile-centric context recognition systems, which are able to sense and analyze the context of the carrier so as to provide an appropriate level of service. As nonintrusive autonomous sensing and context recognition are desirable characteristics of a personal sensing system; efforts have been made to develop opportunistic sensing techniques on mobile phones. The resulting combination of these approaches has ushered in a new realm of applications, namely opportunistic user context recognition with mobile phones. This article surveys the existing research and approaches towards realization of such systems. In doing so, the typical architecture of a mobile-centric user context recognition system as a sequential process of sensing, preprocessing, and context recognition phases is introduced. The main techniques used for the realization of the respective processes during these phases are described, and their strengths and limitations are highlighted. In addition, lessons learned from previous approaches are presented as motivation for future research. Finally, several open challenges are discussed as possible ways to extend the capabilities of current systems and improve their real-world experience

Improving Propagation Modeling in Urban Environments for Vehicular Ad Hoc Networks

Developing applications, particularly real-time applications, for wireless vehicular ad hoc networks (VANETs) requires a reasonable assurance of the likely performance of the network, at the least in terms of packet loss ratios and end-to-end delay. Because wireless propagation strongly influences performance, particularly in an urban environment, this paper improves on simpler propagation models for simulations by augmenting ray-tracing-derived models of propagation. In the non-line-of-sight (NLOS) component, the propagation distance is more closely calculated according to the reflection distance, the effect of roadside obstacles is included, and for the modeling of fast fading, a phase factor is introduced, all without necessarily overly increasing the computational load. In the line-of-sight (LOS) component, as well as the roadside obstacle modeling, single and double reflections from roadside buildings are added to the standard two-ray ground-propagation model, the distribution of vehicles within a street segment is used to more closely model the ground reflection ray, and the reflection coefficient is also accordingly adjusted to account for reflections from vehicles. The results have been compared with widely used measurement studies of city streets in the literature, which have confirmed the overall advantage of the improvements, particularly in the case of the NLOS component. A simulation case study shows that, in general, optimistic performance predictions of packet loss occur with the two-ray ground-propagation model when indiscriminately applied. This paper therefore represents a way forward for VANET wireless channel modeling in simulations

Improving Propagation Modeling in Urban Environments for Vehicular Ad Hoc Networks

Developing applications, particularly real-time applications, for wireless vehicular ad hoc networks (VANETs) requires a reasonable assurance of the likely performance of the network, at the least in terms of packet loss ratios and end-to-end delay. Because wireless propagation strongly influences performance, particularly in an urban environment, this paper improves on simpler propagation models for simulations by augmenting ray-tracing-derived models of propagation. In the non-line-of-sight (NLOS) component, the propagation distance is more closely calculated according to the reflection distance, the effect of roadside obstacles is included, and for the modeling of fast fading, a phase factor is introduced, all without necessarily overly increasing the computational load. In the line-of-sight (LOS) component, as well as the roadside obstacle modeling, single and double reflections from roadside buildings are added to the standard two-ray ground-propagation model, the distribution of vehicles within a street segment is used to more closely model the ground reflection ray, and the reflection coefficient is also accordingly adjusted to account for reflections from vehicles. The results have been compared with widely used measurement studies of city streets in the literature, which have confirmed the overall advantage of the improvements, particularly in the case of the NLOS component. A simulation case study shows that, in general, optimistic performance predictions of packet loss occur with the two-ray ground-propagation model when indiscriminately applied. This paper therefore represents a way forward for VANET wireless channel modeling in simulations

A Fast Calibration Method for Triaxial-Magnetometers

This paper presents a novel iterative calibration algorithm for tri-axial magnetometers. The proposed algorithm estimates and compensates the effects of deterministic interference parameters using only nine distinct measurements. The simulation results confirm that the proposed method outperforms the conventional ellipsoid fitting based models in terms of both accuracy and reliability even with the presence of a moderate wideband noise. The algorithm also achieves fast convergence , which makes it suitable for real-time application

A Survey on Smartphone-based Systems for Opportunistic User Context Recognition

The ever-growing computation and storage capability of mobile phones have given rise to mobile-centric context recognition systems, which are able to sense and analyze the context of the carrier so as to provide an appropriate level of service. As nonintrusive autonomous sensing and context recognition are desirable characteristics of a personal sensing system; efforts have been made to develop opportunistic sensing techniques on mobile phones. The resulting combination of these approaches has ushered in a new realm of applications, namely opportunistic user context recognition with mobile phones. This article surveys the existing research and approaches towards realization of such systems. In doing so, the typical architecture of a mobile-centric user context recognition system as a sequential process of sensing, preprocessing, and context recognition phases is introduced. The main techniques used for the realization of the respective processes during these phases are described, and their strengths and limitations are highlighted. In addition, lessons learned from previous approaches are presented as motivation for future research. Finally, several open challenges are discussed as possible ways to extend the capabilities of current systems and improve their real-world experience