Very Long Baseline Interferometry in Italy Wide-field VLBI imaging and astrometry and prospects for an Italian VLBI network including the Sardinia Radio Telescope

In this thesis the use of widefield imaging techniques and VLBI observations with a limited number of antennas are explored. I present techniques to efficiently and accurately image extremely large UV datasets. Very large VLBI datasets must be reduced into multiple, smaller datasets if today’s imaging algorithms are to be used to image them. I present a procedure for accurately shifting the phase centre of a visibility dataset. This procedure has been thoroughly tested and found to be almost two orders of magnitude more accurate than existing techniques. Errors have been found at the level of one part in 1.1 million. These are unlikely to be measurable except in the very largest UV datasets. Results of a four-station VLBI observation of a field containing multiple sources are presented. A 13 gigapixel image was constructed to search for sources across the entire primary beam of the array by generating over 700 smaller UV datasets. The source 1320+299A was detected and its astrometric position with respect to the calibrator J1329+3154 is presented. Various techniques for phase calibration and imaging across this field are explored including using the detected source as an in-beam calibrator and peeling of distant confusing sources from VLBI visibility datasets. A range of issues pertaining to wide-field VLBI have been explored including; parameterising the wide-field performance of VLBI arrays; estimating the sensitivity across the primary beam both for homogeneous and heterogeneous arrays; applying techniques such as mosaicing and primary beam correction to VLBI observations; quantifying the effects of time-average and bandwidth smearing; and calibration and imaging of wide-field VLBI datasets. The performance of a computer cluster at the Istituto di Radioastronomia in Bologna has been characterised with regard to its ability to correlate using the DiFX software correlator. Using existing software it was possible to characterise the network speed particularly for MPI applications. The capabilities of the DiFX software correlator, running on this cluster, were measured for a range of observation parameters and were shown to be commensurate with the generic performance parameters measured. The feasibility of an Italian VLBI array has been explored, with discussion of the infrastructure required, the performance of such an array, possible collaborations, and science which could be achieved. Results from a 22 GHz calibrator survey are also presented. 21 out of 33 sources were detected on a single baseline between two Italian antennas (Medicina to Noto). The results and discussions presented in this thesis suggest that wide-field VLBI is a technique whose time has finally come. Prospects for exciting new science are discussed in the final chapter.

UMTS base station-like exposure, well-being, and cognitive performance

BACKGROUND: Radio-frequency electromagnetic fields (RF EMF) of mobile communication systems are widespread in the living environment, yet their effects on humans are uncertain despite a growing body of literature. OBJECTIVES: We investigated the influence of a Universal Mobile Telecommunications System (UMTS) base station-like signal on well-being and cognitive performance in subjects with and without self-reported sensitivity to RF EMF. METHODS: We performed a controlled exposure experiment (45 min at an electric field strength of 0, 1, or 10 V/m, incident with a polarization of 45 degrees from the left back side of the subject, weekly intervals) in a randomized, double-blind crossover design. A total of 117 healthy subjects (33 self-reported sensitive, 84 nonsensitive subjects) participated in the study. We assessed well-being, perceived field strength, and cognitive performance with questionnaires and cognitive tasks and conducted statistical analyses using linear mixed models. Organ-specific and brain tissue-specific dosimetry including uncertainty and variation analysis was performed. RESULTS: In both groups, well-being and perceived field strength were not associated with actual exposure levels. We observed no consistent condition-induced changes in cognitive performance except for two marginal effects. At 10 V/m we observed a slight effect on speed in one of six tasks in the sensitive subjects and an effect on accuracy in another task in nonsensitive subjects. Both effects disappeared after multiple end point adjustment. CONCLUSIONS: In contrast to a recent Dutch study, we could not confirm a short-term effect of UMTS base station-like exposure on well-being. The reported effects on brain functioning were marginal and may have occurred by chance. Peak spatial absorption in brain tissue was considerably smaller than during use of a mobile phone. No conclusions can be drawn regarding short-term effects of cell phone exposure or the effects of long-term base station-like exposure on human health.

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Real-time localization using software defined radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.