Device-Free Targets Tracking with Sparse Sampling: A Kronecker Compressive Sensing Approach
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- YANG Sixing
- College of Communications Engineering, Army Engineering University of PLA
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- GUO Yan
- College of Communications Engineering, Army Engineering University of PLA
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- YU Dongping
- College of Communications Engineering, Army Engineering University of PLA
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- QIAN Peng
- College of Communications Engineering, Army Engineering University of PLA
抄録
<p>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.</p>
収録刊行物
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- IEICE Transactions on Communications
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IEICE Transactions on Communications E102.B (10), 1951-1959, 2019-10-01
一般社団法人 電子情報通信学会
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詳細情報 詳細情報について
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- CRID
- 1390282752340465024
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- NII論文ID
- 130007722129
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- ISSN
- 17451345
- 09168516
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可