| Paper ID | SAM-2.1 |
| Paper Title |
Joint DOD and DOA Estimation in Slow-Time MIMO Radar via PARAFAC Decomposition |
| Authors |
Feng Xu, Beijing Institute of Technology, China; Sergiy A. Vorobyov, Aalto University, Finland; Xiaopeng Yang, Beijing Institute of Technology, China |
| Session | SAM-2: Direction of Arrival Estimation 2 |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Sensor Array and Multichannel Signal Processing: [SAM-DOAE] Direction of arrival estimation and source localization |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
We develop a new tensor model for slow-time multiple-input multiple-output (MIMO) radar and apply it for joint DOD and DOA estimation. This tensor model aims to exploit the independence of phase modulation matrix and receive array in the received signal for slow-time MIMO radar. Such tensor can be decomposed into two tensors of different ranks, one of which has identical structure to that of the conventional tensor model for MIMO radar, and the other contains all phase modulation values used in the transmit array. We then develop a modification of the alternating least squares algorithm to enable parallel factor decomposition of tensors with extra constants. The Vandermonde structure of the transmit and receive steering matrices (if both arrays are uniform and linear) is then utilized to obtain angle estimates from factor matrices. The multi-linear structure of the received signal is maintained to take advantage of tensor-based angle estimation algorithms, while the shortage of samples in Doppler domain for slow-time MIMO radar is mitigated. As a result, the joint DOD and DOA estimation performance is improved as compared to existing angle estimation techniques for slow-time MIMO radar. Simulation results verify the effectiveness of the proposed method. |
