講座名稱：A Unified Estimator for Near-Field and Far-Field Localization Using TDOA

講座時間：2020-01-06 9:30:00

講座地點：北校區新科技樓1012

講座人：Dominic K. C. Ho

講座人介紹：

Dominic K.C.Ho教授現任職于美國密蘇里大學電氣工程與計算機科學系教授，IEEE Fellow，曾擔任IEEE Trans. on Signal Processing、IEEE Signal Processing Letters副主編，IEEE信號處理協會傳感器陣列和多通道(SAM)技術委員會主席(2015年)，IEEE ICASSP技術聯合主席(2016年)，在信號處理領域有很深的學術造詣并享有廣泛的國際名聲；是22項關于無線通信、地理位置定位和信號處理領域的美國、加拿大、歐洲專利發明人，發表IEEE TSP/TWC等期刊論文117篇、IEEE ICASSP等會議論文160篇，75項國際電聯ITU-T標準或提案的起草人或報告人，美國國家自然科學基金長期資助人員；同時擔任我校信號定位與無線通信領域國際合作專家，是西安電子科技大學客座教授，聯合研究方向包括面向人工智能的固態體定位系統、天基頻譜感知目標定位系統等。

講座內容：

Localization of an object is fundamental in many engineering applications. Using of a number of sensors and observing the signal arrival time differences, we are able to determine the unique coordinates of an object if it is not distant. On the other hand, we can only obtain its DOA if it is far away. One has to know if the object is near or far to apply point or DOA estimation and such knowledge is often unavailable. Using a near-field model to locate a distant object will yield an unreasonable result caused by the thresholding effect and applying a far-field model to a near object will produce a significant DOA bias. This talk revisits the HBB Bound that illustrates the thresholding phenomenon in locating the point position of an object as its range to the sensor array increases. A unified TDOA positioning estimator based on an iterative implementation of the MLE is next introduced, which does not require the knowledge if the object is near or far. It automatically generates a point position if the object is near and yields the DOA if it is far. An initialization to the MLE based on a solution by the semidefinite relaxation is proposed. Simulation examples validate the good performance of the proposed estimator.

主辦單位：通信工程學院