321 / 2020-01-06 11:37:00
Sample complexity trade-offs for synthetic aperture based high-resolution estimation and detection
Sparse Array; Difference Co-Array; Array Motion; Synthetic Array; Sample Complexity Trade-Off
全文录用
Heng Qiao / University of California, San Diego, USA
Pulak Sarangi / University of California, San Diego, USA
Yazeed Alnumay / University of California, San Diego, USA
Piya Pal / University of California, San Diego, USA
This paper critically examines the potential performance benefits offered by motion of sparse arrays for direction-of-arrival (DOA) estimation. The motivation behind utilizing array motion is to increase the number of consecutive difference lags. However, creating a synthetic array also requires more temporal measurements compared to the static (non-synthetic) array. For the first time, we rigorously analyze the trade-off between the required number of temporal samples and the length of the difference co-array to understand when synthetic arrays offer distinct advantages. As a concrete result, we show that if the ratio of the number of consecutive lags of the difference coarray of sparse arrays with and without motion is above a universal threshold, the synthetic array outperforms its non-synthetic counterpart and has a smaller estimation error. Our claims are demonstrated both theoretically and through numerical experiments.
重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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