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Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing

Masanari NOTO, Fang SHANG, Shouhei KIDERA, Tetsuo KIRIMOTO

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Summary :

There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth. One of the most promising solutions is the use of compressed sensing (CS) algorithms, which assume only the sparseness of the target distribution but can achieve super-resolution. To preserve the reconstruction accuracy of CS under highly correlated and noisy conditions, we introduce a random resampling approach to process the received signal and thus reduce the coherent index, where the frequency-domain-based CS algorithm is used as noise reduction preprocessing. Numerical simulations demonstrate that our proposed method can achieve super-resolution TOA estimation performance not possible with conventional CS methods.

Publication
IEICE TRANSACTIONS on Communications Vol.E101-B No.6 pp.1513-1520
Publication Date
2018/06/01
Publicized
2017/12/18
Online ISSN
1745-1345
DOI
10.1587/transcom.2017EBP3324
Type of Manuscript
PAPER
Category
Sensing

Authors

Masanari NOTO
  University of Electro-Communications
Fang SHANG
  University of Electro-Communications
Shouhei KIDERA
  University of Electro-Communications
Tetsuo KIRIMOTO
  University of Electro-Communications

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