Global Navigation Satellite Systems (GNSS) is the technology of choice for most position-related applications, when it is available. A GNSS receiver relies on a constellation of satellites to estimate a set of range measures from which to compute its position. These distances are calculated estimating the propagation time that transmitted signals take from each satellite to the receiver. The term GNSS encompasses GPS, Galileo, GLONASS, or Beidou systems among others. The main challenges of GNSS technology arise when operating in complex environments which are either naturally impaired by multipath, shadowing, high dynamics, or ionospheric scintillation; or intentionally/unintentionally interfered. Ushered by an ever increasing demand for availability, accuracy, and reliability, the mitigation of these challenges has steered intense research on advanced receiver design. Remarkably, the progress in this area is tightly coupled with the increased adoption of the software defined radio (SDR) paradigm within the GNSS community, which allowed for faster transitioning from algorithmic development to real-world testing. This talk will provide a brief introduction to GNSS technology, with focus on the signal processing challenges of receiver design, as well as a discussion of sample research projects where the use of SDR is at the core. The talk will touch upon the GNSS-SDR project (gnss-sdr.org), a free and open source software implementing an end-to-end GNSS receiver. GNSS-SDR has been used in a multitude of projects, some of which will be discussed in this talk, such as the possibility to transform a TV dongle into a GNSS receiver, or localizing and mitigating inferring signals. The main goal of this talk is to highlight the importance of SDR – and its continuous evolution – to boost research activities and, in particular, in the field of satellite-based navigation.
Presenter: Pau Closas received his MS and PhD degrees in electrical engineering from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, in 2003 and 2009, respectively, as well as a MS in Advanced Mathematics from UPC in 2014. He is an Assistant Professor in the Electrical and Computer Engineering Department at Northeastern University, Boston, Massachusetts. His primary areas of interest include statistical signal processing, stochastic filtering, and robust statistics with applications to positioning systems, wireless communications, and mathematical biology. Among other distinctions, he is the recipient of the NSF CAREER Award, the 2014 EURASIP Best PhD Thesis Award, the Ninth Duran Farell Award for Technology Research, and the 2016 ION Early Achievements Award in recognition to his contributions to navigation systems and signal processing fields. He has served in the organization of flagship IEEE conferences and journals.