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

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  • NOTO Masanari
    Graduate School of Informatics and Engineering, University of Electro-Communications
  • SHANG Fang
    Graduate School of Informatics and Engineering, University of Electro-Communications
  • KIDERA Shouhei
    Graduate School of Informatics and Engineering, University of Electro-Communications
  • KIRIMOTO Tetsuo
    Graduate School of Informatics and Engineering, University of Electro-Communications

Abstract

<p>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.</p>

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