Topic (报告题目)：Kalman Filtering and Optimal Sensor Motion in Bearings-Only Tracking
Reporter (报告人)：Professor Kutluyil Dogancay， 南澳大学
Times (时间)：Friday, November 11, 1:30pm-2:30pm
VooV Meeting ID (腾讯会议): 139-291-184 orhttps://meeting.tencent.com/dm/2CVl2UcLpwtH
报告简介：This short talk is devoted to discuss Kalman Filtering and Optimal Sensor Motion in Bearings-Only Tracking. Target tracking is an important practical problem with many civilian and military applications. The objective of target tracking is to estimate the location, velocity and acceleration of a target from noisy sensor data collected by a moving observer or several physically dispersed stationary observers. The sensor data typically comprise bearing angle (angle of arrival), time difference of arrival or Doppler frequency measurements. In passive bearings-only target tracking, the observer “listens” for signals emitted by a target in order to acquire bearing data. The moving observer, which is also known as the ownship, can be an aircraft, a ship or an unmanned aerial vehicle (UAV).
Introduction of lecture (报告人简介)：Kutluyil Dogancay received the BS degree with honours in electrical and electronic engineering from Bosphorus University in 1989, the MSc degree in communications and signal processing from Imperial College, University of London, in 1992, and the PhD degree in telecommunications engineering from The Australian National University in 1996. Since November 1999 he has been with University of South Australia, where he is currently a professorial lead in the UniSA STEM Unit. Between 2018-2020 he was Associate Head: Research and Innovation in School of Engineering. In 2012 he was appointed Assistant Dean of Research Education for the Division of Information Technology, Engineering and the Environment, and served in this role until 2015. During that time, he also acted as Dean of Research for a total period of 13 months. Professor Dogancay is the Editor-in-Chief of Digital Signal Processing, Elsevier.
Professor Dogancay's research interests telecommunication applications of statistical and adaptive signal processing. His research has been funded by the ARC, DST Group, and industry through several competitive grants and research agreements. He has published more than 200 refereed journal articles, conference papers, and two books (Signal Processing for Multistatic Radar Systems: Adaptive Waveform Selection, Optimal Geometries and Pseudolinear Tracking Algorithms, and Partial-Update Adaptive Signal Processing: Design, Analysis and Implementation). He holds two US patents jointly with Tellabs Inc on partial-update adaptive filters.
