2D-DOD and 2D-DOA Estimation Using Sparse L-Shaped EMVS-MIMO Radar

作者：Wen, Fangqing^*; Shi, Junpeng; He, Jin; Truong, Trieu-Kien

来源：IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(2): 2077-2084.

DOI：10.1109/TAES.2022.3208858

• Radar
• Estimation
• Sensor arrays
• Apertures
• Electromagnetics
• Direction-of-arrival estimation
• US Department of Defense
• 2-D direction finding
• electromagnetic vector sensor (EMVS)
• multiple-input multiple-output (MIMO) radar
• sparse array

It is well known that electromagnetic vector sensor (EMVS)-multiple-input multiple-output (MIMO) radar is an emerging technique that allows for 2D-direction-of-departure (DOD) and 2D-direction-of-arrival (DOA) estimation. Unfortunately, existing array geometries on the EMVS-MIMO radar can rarely reach a good compromise between the estimation accuracy and the computational burden. This article is aimed at proposing an L-shaped sparse array topology for a bistatic EMVS-MIMO radar, whose interelement distance is much larger than half-wavelength. A fast algorithm is proposed herein to estimate the 2D-DOD and 2D-DOA. First, the direction cosine estimates are obtained via the rotational invariance properties of the sparse subarrays, which are ambiguous yet exhibit high-resolution. Thereafter, the direction cosine estimates are achieved via the vector cross-product of the normalized Poynting vectors, which are unambiguous but have low-resolution. The unambiguous high-resolution direction cosine estimates are determined by combining the previous results, following which the 2D-DOD and 2D-DOA can be easily recovered. It is shown that the proposed framework can obtain a better accuracy of estimation than the other existing methods. Moreover, it is more flexible than the current sparse array methodologies. Finally, the theoretical derivations have been validated by simulation results.

• 单位
  上海交通大学