摘要
The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.
The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.
基金
supported by the National Natural Science Foundation of China(61101173)
作者简介
Corresponding author. Wei Xia was born in 1980. He received his B.S. degree from University of Electronic Science and Technology of China （UESTC）, in 2002 in communication engineering. He received his M.S. degree and Ph.D. degree from UESTC, in 2005 and 2008, respectively, both in electronic engineering. From January 2009 to June 2011, he was a lecturer in the School of Electronic Engineering at UESTC.Since July 2011, he has been with the School of Electronic Engi- neering at UESTC, where he is an associate professor. His general research interests include statistical signal processing, adaptive signal processing, radar signal processing, and advanced implementation techniques of signal processing algorithm. E-mail： wx@uestc.edu.cnWei Liu was born in 1990. He received his B.S. degree in Hubei University of Automotive Technology （HUAT）. He is currently pursuing his M.S. degree in University of Electronic Science and Technology of China （UESTC）. His research areas of interest include adaptive signal processing, distributed optimization, sensor networks and passive localization. E-mail： liuweiqcxy@163.comLingfeng Zhu was born in 1991. He received his B.S. degree in University of Electronic Science and Technology of China （UESTC）. He is currently pursuing his M.S. degree in University of Electronic Science and Technology of China （UESTC）. His research areas of interest include adaptive signal processing, distributed optimization, sensor networks and passive localization. E-mail： ifeng1050@163.com
