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Open AccessArticle

A High-Resolution Joint Angle-Doppler Estimation Sub-Nyquist Radar Approach Based on Matrix Completion

1
School of Information Engineering, Lingnan Normal University, Zhanjiang 524000, China
2
Huawei Technologies Co., Ltd., Shenzhen 518000, China
*
Author to whom correspondence should be addressed.
Information 2019, 10(4), 124; https://doi.org/10.3390/info10040124
Received: 8 January 2019 / Revised: 29 March 2019 / Accepted: 2 April 2019 / Published: 4 April 2019
(This article belongs to the Section Information Processes)
In order to reduce power consumption and save storage capacity, we propose a high-resolution sub-Nyquist radar approach based on matrix completion (MC), termed as single-channel sub-Nyquist-MC radars. While providing the high-resolution joint angle-Doppler estimation, this proposed radar approach minimizes the number of samples in all three dimensions, that is, the range dimension, the pulse dimension (also named temporal dimension), and the spatial dimension. In range dimension, we use a single-channel analog-to-information converter (AIC) to reduce the number of range samples to one; in both spatial and temporal dimensions, we employ a bank of random switch units to regulate the AICs, which greatly reduce the number of spatial-temporal samples. According to the proposed sampling scheme, the samples in digital processing center forwarded by M receive nodes and N pulses are only a subset of the full matrix of size M times N. Under certain conditions and with the knowledge of the sampling scheme, the full matrix can be perfectly recovered by using MC techniques. Based on the recovered full matrix, this paper addresses the problem of the high-resolution joint angle-Doppler estimation by employing compressed sensing (CS) techniques. The properties and performance of the proposed approach are demonstrated via simulations. View Full-Text
Keywords: compressed sensing radar; sub-Nyquist sampling; matrix completion; array signal processing; recovery algorithm compressed sensing radar; sub-Nyquist sampling; matrix completion; array signal processing; recovery algorithm
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Wang, Q.; Sun, Y. A High-Resolution Joint Angle-Doppler Estimation Sub-Nyquist Radar Approach Based on Matrix Completion. Information 2019, 10, 124.

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