TY - GEN
T1 - Reduced complexity FFT-based DOA and DOD estimation for moving target in bistatic MIMO radar
AU - Ali, Hussain
AU - Ahmed, Sajid
AU - Al-Naffouri, Tareq Y.
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): URF/1/1713-01-01
Acknowledgements: URF/1/1713-01-01, KAUST
PY - 2016/6/24
Y1 - 2016/6/24
N2 - In this paper, we consider a bistatic multiple-input multiple-output (MIMO) radar. We propose a reduced complexity algorithm to estimate the direction-of-arrival (DOA) and direction-of-departure (DOD) for moving target. We show that the calculation of parameter estimation can be expressed in terms of one-dimensional fast-Fourier-transforms which drastically reduces the complexity of the optimization algorithm. The performance of the proposed algorithm is compared with the two-dimension multiple signal classification (2D-MUSIC) and reduced-dimension MUSIC (RD-MUSIC) algorithms. It is shown by simulations, our proposed algorithm has better estimation performance and lower computational complexity compared to the 2D-MUSIC and RD-MUSIC algorithms. Moreover, simulation results also show that the proposed algorithm achieves the Cramer-Rao lower bound. © 2016 IEEE.
AB - In this paper, we consider a bistatic multiple-input multiple-output (MIMO) radar. We propose a reduced complexity algorithm to estimate the direction-of-arrival (DOA) and direction-of-departure (DOD) for moving target. We show that the calculation of parameter estimation can be expressed in terms of one-dimensional fast-Fourier-transforms which drastically reduces the complexity of the optimization algorithm. The performance of the proposed algorithm is compared with the two-dimension multiple signal classification (2D-MUSIC) and reduced-dimension MUSIC (RD-MUSIC) algorithms. It is shown by simulations, our proposed algorithm has better estimation performance and lower computational complexity compared to the 2D-MUSIC and RD-MUSIC algorithms. Moreover, simulation results also show that the proposed algorithm achieves the Cramer-Rao lower bound. © 2016 IEEE.
UR - http://hdl.handle.net/10754/621350
UR - http://ieeexplore.ieee.org/document/7472232/
UR - http://www.scopus.com/inward/record.url?scp=84973324988&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2016.7472232
DO - 10.1109/ICASSP.2016.7472232
M3 - Conference contribution
SN - 9781479999880
SP - 3021
EP - 3025
BT - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -