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

Masanari NOTO
Shouhei KIDERA

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
super-resolution TOA estimation,  compressed sensing (CS),  radar signal processing,  random re-sampling,  

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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.