Device-Free Targets Tracking with Sparse Sampling: A Kronecker Compressive Sensing Approach

Sixing YANG  Yan GUO  Dongping YU  Peng QIAN  

Publication
IEICE TRANSACTIONS on Communications   Vol.E102-B   No.10   pp.1951-1959
Publication Date: 2019/10/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2018DRP0010
Type of Manuscript: Special Section PAPER (Special Section on Exploring Drone for Mobile Sensing, Coverage and Communications: Theory and Applications)
Category: 
Keyword: 
device-free localization,  Kronecker compressive sensing,  sparse sampling,  target tracking,  

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Summary: 
We research device-free (DF) multi-target tracking scheme in this paper. The existing localization and tracking algorithms are always pay attention to the single target and need to collect a large amount of localization information. In this paper, we exploit the sparse property of multiple target locations to achieve target trace accurately with much less sampling both in the wireless links and the time slots. The proposed approach mainly includes the target localization part and target trace recovery part. In target localization part, by exploiting the inherent sparsity of the target number, Compressive Sensing (CS) is utilized to reduce the wireless links distributed. In the target trace recovery part, we exploit the compressive property of target trace, as well as designing the measurement matrix and the sparse matrix, to reduce the samplings in time domain. Additionally, Kronecker Compressive Sensing (KCS) theory is used to simultaneously recover the multiple traces both of the X label and the Y Label. Finally, simulations show that the proposed approach holds an effective recovery performance.