Particle filtering has emerged as one of the most exciting developments in sequential signal processing in the last two decades. It has become a methodology of choice for resolving most complex problems of stochastic filtering. In this presentation, the basics of particle filtering and its properties will be briefly reviewed. Then an overview of various advances of the methodology in recent years will be provided. Current challenges and the future of particle filtering will also be discussed.
Petar M. Djurić received the B.S. and M.S. degrees in electrical engineering from the University of Belgrade, Belgrade, Yugoslavia, and the Ph.D. degree in electrical engineering from the University of Rhode Island, Kingston, RI, USA. He is currently a Professor with the Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA. His research has been in the area of signal and information processing with primary interest in signal analysis, modeling, detection, and estimation; Monte Carlo-based methods; Bayesian theory; machine learning; network science; applications to biomedicine; Radio Frequency Identification. He has been invited to lecture at many universities in the United States and overseas. Prof. Djurić was a recipient of the IEEE Signal Processing Magazine Best Paper Award in 2007 and the EURASIP Technical Achievement Award in 2012. He is the Editor-in-Chief of the IEEE Transactions on Signal and Information Processing over Networks. Prof. Djurić is a Fellow of the IEEE and EURASIP.