Talk 5: Target Detection Based on Passive Radar

Speaker: Lu Sun

Affiliation: Dalian Maritime University

Academic title: Associate Professor


We proposed a new algorithm for range-Doppler estimation in PBR within the framework of sparse recovery in compressed sensing. By using a simulated scenario, we show that the algorithm is effective to reduce the masking effects of strong targets over weak ones. In addition, we have implemented the PBR system to collect real data and validate the proposed algorithms based on the real data. Compared with the conventional beamforming, our proposed method has better estimation performance for direct path. When the beam we observe and the beam of the direct path are too closed, compared with the beamforming, more number of frames can be observed using our proposed method. Since the effect among the target has been reduced, the M-OMP has better estimation performance for range-Doppler-angle estimation compared with the conventional MF method, especially for DOA estimation.


Lu Sun received the B.S. degree and the Ph.D. degree in the School of Software from Dalian University of Technology, Dalian, China, in 2013 and 2019, respectively. She is currently an Associate Professor of Institute of Information Science Technology, Dalian Maritime University, Dalian, China. Her current research interests include passive radar detection, resource allocation and wireless power transfer.


Important dates

Paper Submission Deadline:
30 September, 2023
Paper Acceptance Notification:
20 October, 2023
Camera-ready Paper Submission:
5 November, 2023
Registration open date:
20 October, 2023
Conference Date:
3-5 December, 2023

Remaining days till

IRC 2023


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