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Tensor Decomposition Based DOA Estimation for Transmit Beamspace MIMO Radar
- Source :
- EUSIPCO
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- 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.
- Subjects :
- Computer science
MIMO
Direction of arrival
020206 networking & telecommunications
02 engineering and technology
law.invention
Matrix (mathematics)
Signal-to-noise ratio
law
0202 electrical engineering, electronic engineering, information engineering
Rotational invariance
020201 artificial intelligence & image processing
Tensor
Radar
Algorithm
Energy (signal processing)
Computer Science::Information Theory
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 28th European Signal Processing Conference (EUSIPCO)
- Accession number :
- edsair.doi...........4946e7e54bbbce736e3a0ee45414ab7e
- Full Text :
- https://doi.org/10.23919/eusipco47968.2020.9287411