KAUST, Kindgdom of Saudi Arabia.
Towards Robust & Accurate Localization: A Manifold Optimization Approach
Localization is an essential requirement for many applications (commercial, retail, military, scientific,... etc.) and in a variety of environments (in-doors, outdoors, space, underwater, and even underground). This talk will overview some of my current work in localization and navigation focusing on indoor and satellite positioning. The talk will show how the structure or constraints of the localization problem can help achieve very accurate localization (e.g. millimeter level indoors) that is robust to Doppler, multipath, and shadowing. Specifically, we will demonstrate how tools from Riemannian (manifold) optimization can be used to solve the localization problem with higher accuracy and lower complexity compared to the state of the art. The talk will end with demos of various localization-related applications that my group is pursuing in smart health and smart cities.
Tareq Al-Naffouri received the B.S. degrees in mathematics and electrical engineering (with first honors) from King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, the M.S. degree in electrical engineering from the Georgia Institute of Technology, Atlanta, and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, in 2004. He was a visiting scholar at California Institute of Technology, Pasadena, CA in 2005 and summer 2006 and a Fulbright scholar at the University of Southern California in 2008. He is currently a Professor at the Electrical Engineering Department, King Abdullah University of Science and Technology (KAUST). His research interests lie in the areas of sparse, adaptive, and statistical signal processing and their applications to wireless communications and localization, machine learning, and network information theory. He has over 300 publications in journal and conference proceedings and 20 issued/pending patents.