NDLI: Sparse Representation Based Distributed Multisensor Track Fusion

Content Provider	IEEE Xplore Digital Library
Author	Wang Huan Sun Jinping
Copyright Year	2015
Description	Author affiliation: Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China (Wang Huan; Sun Jinping)
Abstract	In the distributed multisensory information fusion system, each local sensor independently forms local tracks, and multisensory track fusion refers to fusing multiple local tracks that represent the same target into one global track. By studying the theory of multisensory track fusion and signal sparse representation, a sparse representation based multisensory track fusion algorithm is proposed. This new algorithm first obtains a noisy dictionary and a noise-free dictionary by sample tracks. At each scan, the state vectors of local tracks from the same target are rewritten as a vector, and then the sparse representation coefficients of the vector in noisy dictionary are computed. At last, the global state vector at this scan is obtained by the sparse representation coefficients and noise-free dictionary. Simulation results illustrate that the fusion results of the new algorithm are better than that of Linear Minimum Mean-Square Error (LMMSE).
Sponsorship	Tongji Univ.
Starting Page	476
Ending Page	479
File Size	152563
Page Count	4
File Format	PDF
e-ISBN	9781467368506
DOI	10.1109/ICISCE.2015.110
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Dictionaries Target tracking Multisensor Simulation Noise Data integration Distributed Sparse representation Noise measurement Track fusion
Content Type	Text
Resource Type	Article

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