Lang White

Biography

Lang White obtained the degrees of B.Sc., B.E. (hons) and Ph.D. (Electrical Engineering) from the University of Queensland, Brisbane Australia in 1984, 1985 and 1989 respectively. From 1986-1999 he worked as a Research Scientist at the Defence Science and Technology Organisation Australia in the areas of radar and communications electronic warfare. Since 1999 he has been Professor in the School of Electrical and Electronic Engineering at the University of Adelaide. From 2002-2006, he was a Fellow with National ICT Australia Ltd. Lang White obtained the degrees of B.Sc., B.E. (hons) and Ph.D. (Electrical Engineering) from the University of Queensland, Brisbane Australia in 1984, 1985 and 1989 respectively. From 1986-1999 he worked as a Research Scientist at the Defence Science and Technology Organisation Australia in the areas of radar and communications electronic warfare. Since 1999 he has been Professor in the School of Electrical and Electronic Engineering at the University of Adelaide. From 2002-2006, he was a Fellow with National ICT Australia Ltd.

Research Interest

1. Statistical modelling and estimation for hidden reciprocal chains (HRCs) HRCs are non-causal generalisations of hidden Markov chains and are one-dimensiona Markov random fields, although reciprocal processes are not, in general, Markovian. In this research, we investigate modelling, optimal state estimation, parameter estimation and model classification for HRCs. Applications addressed include "destination-aware" target tracking and the forensic analysis of "pattern-of-life" problems. Collaborators : Dr Francesco Carravetta (IASI-CNR, Italy) and Prof Vikram Krishnamurthy (UBC, Canada).   2. Signal subspace methods for sensor array processing of temporally correlated signals This research is motivated by the question of whether temporal correlation in signals incident of a sensor array can be used to improve source localisation and classification. Advances in computational power mean that previously neglected techniques such as maximum likelihood estimation now become feasible. Recent results concerning the asymptotic consistency of certain estimators (Generalised Statistical Analysis) has also raised the question of whether these approaches can be used in signal subspace based methods such as ESPRIT. This project investigates a range of questions related to these two problems. Collaborators : Prof Peter Sherman (Iowa State Univ., USA), Defence Science and Technology Organisation Australia.   3. Markov Decision Processes and State Aggregation This work is concerned with the development of sub-optimal control strategies for very large Markov decision processes, where state aggregation is used to reduce dimensionality. Models considered include Quasi Birth-Death processes and optimally lumped processes. 4. Signal processing for GPS interference mitigation Funded by an ARC Linkage grant, and building on previous work cinducted in the School, this work is concerned with localisation and mitigation of jammers/spoofers in the GPS bands. Much critical infrastructure (e.g. aviation, ports, mining) relies on GPS localisation and the issue of dealing with deliberate or unintentional interference is very important. This project teams with the University of NSW and GPSat Systems.