Sample complexity trade-offs for synthetic aperture based high-resolution estimation and detection
ID:93 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:377 Oral Presentation

Start Time:2020-06-08 15:20(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS09Aperture Extension And Synthetic Techniques For High-Resolution Detection And Estimation

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Abstract
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.
Keywords
Sparse Array; Difference Co-Array; Array Motion; Synthetic Array; Sample Complexity Trade-Off
Speaker
Heng Qiao
University of California, San Diego, USA

Submission Author
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
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    Jun 08

    2020

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    Jun 11

    2020

  • Jan 12 2020

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  • Apr 15 2020

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  • Dec 31 2020

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