Tensor Decomposition Based DOA Estimation for Transmit Beamspace MIMO Radar

The detection and localization of multiple targets is a fundamental research area for multiple input multiple output (MIMO) radar. In many civilian applications of MIMO technology, for example, automotive radar, high resolution direction of arrival (DOA) estimation is required. In this paper, a novel DOA estimation algorithm based on tensor decomposition is proposed for collocated transmit beamspace MIMO radar. First, we introduce the flipped-conjugate version of the transmit beamspace matrix, which focuses the transmit energy into fixed region. This can increase the signal to noise ratio (SNR) of targets. Then we reshape the received data into a tensor form, the structure of which provides the estimations of the transmit and receive steering matrices. The alternating least squares (ALS) algorithm is applied to find the tensor components. The DOA estimation is conducted in transmitters via the rotational invariance property achieved by beamspace matrix. It is proved that at most M - 2 grating lobes exist during the process of DOA estimation, where M is the number of the transmitters. These grating lobes can be eliminated by finite trials of spectrum search. The performance of our proposed DOA estimation method surpasses several conventional algorithms in terms of accuracy and resolution.

Automated summary

This paper proposes a novel DOA estimation algorithm based on tensor decomposition for collocated transmit beamspace MIMO radar, which increases the signal to noise ratio by introducing the flipped-conjugate version of the transmit beamspace matrix. The alternating least squares (ALS) algorithm is utilized to find tensor components and grating lobes can be eliminated by finite trials of spectrum search. The performance of the proposed DOA estimation method outperforms several conventional algorithms in terms of accuracy and resolution.