Abstract
In this paper, we suggest an efficient algorithm for joint direction-of-arrival (DOA) and direction-of-departure (DOD) estimation in bistatic multiple-input multiple-output (MIMO) radar with unknown mutual coupling. Based on the inherent structure of mutual coupling matrix of MIMO radar array, we firstly extract the data without mutual coupling effects from the outputs of the matched filters. Then, the signal model is transformed by Kronecker product based transformation to realize the block sparse representation of DOD and DOA respectively. This avoids the need for two-dimensional grid dividing in the spatial domain, resulting in a significant reduction in computational complexity. Moreover, considering scenarios involving grid mismatch, off-grid vector is introduced into the block sparse model respectively. Finally, an additional process is performed to pair the DOD and DOA estimates. Simulation results demonstrate the superiority of the proposed algorithm over several existing methods.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China under Grant 62171089, and in part by the Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0497.
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He, M., Ren, C., Liu, R. et al. Reduced-Dimensional Block Sparse Angle Estimation for Bistatic MIMO Radar with Unknown Mutual Coupling. Wireless Pers Commun 138, 1423–1438 (2024). https://doi.org/10.1007/s11277-024-11462-z
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DOI: https://doi.org/10.1007/s11277-024-11462-z