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Keywords = random time division multiplexing (Random TDM)

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16 pages, 4933 KB  
Article
Random Time Division Multiplexing Based MIMO Radar Processing with Tensor Completion Approach
by Yuan Zhang, Yixue Qiao, Gang Li, Wei Li and Qing Tian
Sensors 2023, 23(10), 4756; https://doi.org/10.3390/s23104756 - 15 May 2023
Cited by 2 | Viewed by 3008
Abstract
Automotive radar pursues low cost and high performance, and especially hopes to improve the angular resolution under the condition of a limited number of multiple-input–multiple-output (MIMO) radar channels. Conventional time division multiplexing (TDM) MIMO technology has a limited ability to improve the angular [...] Read more.
Automotive radar pursues low cost and high performance, and especially hopes to improve the angular resolution under the condition of a limited number of multiple-input–multiple-output (MIMO) radar channels. Conventional time division multiplexing (TDM) MIMO technology has a limited ability to improve the angular resolution without increasing the number of channels. In this paper, a random time division multiplexing MIMO radar is proposed. First, the non-uniform linear array (NULA) and random time division transmission mechanism are combined in the MIMO system, and then a three-order sparse receiving tensor of a range-virtual aperture-pulse sequence is obtained during echo receiving. Next, this sparse three-order receiving tensor is recovered by using tensor completion technology. Finally, the range, velocity and angle measurements are completed for the recovered three-order receiving tensor signals. The effectiveness of this method is verified via simulations. Full article
(This article belongs to the Section Radar Sensors)
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