The 16th International Conference on Electronics, Communications and Networks (CECNet 2026)

Abstract: Real time and high precision wireless positioning serves as a fundamental supporting technology for smart city, intelligent transportation, Internet of Vehicles, target reconnaissance, unmanned platform coordination and other electronic information and situation awareness applications. Traditional two step wireless localization first estimates intermediate parameters and then solves target positions, which suffers from information loss, performance limitation and target measurement data association ambiguity. Direct localization can obtain target coordinates straightly from raw received signals without intermediate parameter estimation, and it makes full use of signal waveform characteristics to avoid association mismatches. Nevertheless, practical non ideal scenarios bring severe challenges, including low signal to noise ratio caused by long transmission distance, non line of sight propagation, group multi targets, multi band transmitted signals, as well as array manifold and channel model errors.
This report investigates cooperative direct localization technologies coping with the above non ideal conditions. Firstly, a multi constant modulus source direct localization algorithm based on direction of arrival and Doppler shift is proposed, which exploits constant modulus signal properties to boost positioning accuracy under low SNR and small snapshot quantities. Secondly, a time difference of arrival based direct localization approach utilizing known modulation information is presented, where alternating iteration combining discrete symbol optimization and continuous position estimation improves localization performance close to the bound of fully known waveforms. Thirdly, a cooperative direct localization scheme fusing short wave and ultra short wave observations is developed. By jointly processing multi band signals, it extends effective observation baseline and optimizes geometric error ellipses for positioning. Fourthly, a calibration assisted robust direct localization method is designed to mitigate array manifold errors. Known position calibration emitters are adopted in alternating iteration optimization to eliminate estimation bias induced by array imperfections. Furthermore, a deep learning enabled over the horizon target direct localization framework based on bidirectional long short term memory (BiLSTM) network is put forward. The SL BiLSTM model extracts implicit location related features from multi station array signals to counteract complicated and uncertain ionospheric interference. Corresponding signal models, iterative optimization strategies and simulation validations are provided for each method. Simulation results demonstrate that the proposed cooperative direct localization methods achieve superior positioning accuracy compared with conventional two step and non cooperative counterparts, especially under low signal quality non ideal conditions. Finally, prospective research directions are summarized, covering group target cooperative localization under spatio temporal correlation, multi error calibration aided robust localization, bandwidth constrained cooperative direct localization, deep learning based direct tracking and group target tracking techniques.

Biography: DING WANG received his B.S., M.S., and Ph.D. degrees from Information Engineering University in July 2004, July 2007, and December 2011, respectively. From January 2015 to January 2018, he was a Postdoctoral Researcher at Information Engineering University. He is currently a Professor and Ph.D. Supervisor at the School of Information Systems Engineering, Information Engineering University.
He has been supported by the National Natural Science Foundation of China (Grant Nos. 62671620, 62171469, 62071029, 61772548), China Postdoctoral Science Foundation (Grant No. 2016M592989), and Key Scientific and Technological Research Project of Henan Province (Grant No. 192102210092). He was Selected for the Provincial/Ministerial High-Level Science and Technology Talent Program. His research interests include wireless signal cooperative localization and array signal processing.
As the first/corresponding author, he has published more than 80 SCI/Ei-indexed journal papers and 8 monographs as the first author. He has received 3 second-class and 5 third-class Provincial and Ministerial Scientific and Technological Progress Awards, won the F5000 Top Article Award in Outstanding S&T Journals of China in 2020, was selected as a CNKI High-Impact Scholar in 2024, and was selected as one of the Top 1% Most Cited Scholars in China, 2025. He was awarded the Excellent Author & Translator Prize on the 40th Anniversary of the Publishing House of Electronics Industry.