Translator Disclaimer
13 May 2019 Sparsity-based collaborative sensing in a scalable wireless network
Author Affiliations +
In this paper, we propose a collaborative sensing scheme for source localization and imaging in an unmanned aerial vehicle (UAV) network. A two-stage image formation approach, which combines the robust adaptive beamforming technique and sparsity-based reconstruction strategy, is proposed to achieve accurate multi-source localization. In order to minimize the communication traffic in the UAV network, each UAV node only transmits the coarse-resolution image, in lieu of the large volume of raw sampled data. The proposed method maintains the robustness in the presence of model mismatch while providing a high-resolution image.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuimei Zhang, Ammar Ahmed, and Yimin D. Zhang "Sparsity-based collaborative sensing in a scalable wireless network", Proc. SPIE 10989, Big Data: Learning, Analytics, and Applications, 1098904 (13 May 2019);

Back to Top