DFT-Based Closed-form Covariance Matrix and Direct Waveforms Design for MIMO Radar to Achieve Desired Beampatterns
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
KAUST Grant NumberURF/1/1713-01-01
Permanent link to this recordhttp://hdl.handle.net/10754/622718
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AbstractIn multiple-input multiple-out (MIMO) radar, for desired transmit beampatterns, appropriate correlated waveforms are designed. To design such waveforms, conventional MIMO radar methods use two steps. In the first step, the waveforms covariance matrix, R, is synthesized to achieve the desired beampattern. While in the second step, to realize the synthesized covariance matrix, actual waveforms are designed. Most of the existing methods use iterative algorithms to solve these constrained optimization problems. The computational complexity of these algorithms is very high, which makes them difficult to use in practice. In this paper, to achieve the desired beampattern, a low complexity discrete-Fourier-transform based closed-form covariance matrix design technique is introduced for a MIMO radar. The designed covariance matrix is then exploited to derive a novel closed-form algorithm to directly design the finite-alphabet constant-envelope waveforms for the desired beampattern. The proposed technique can be used to design waveforms for large antenna array to change the beampattern in real time. It is also shown that the number of transmitted symbols from each antenna depends on the beampattern and is less than the total number of transmit antenna elements.
CitationBouchoucha T, Ahmed S, Alnaffouri T, Alouini M (2017) DFT-Based Closed-form Covariance Matrix and Direct Waveforms Design for MIMO Radar to Achieve Desired Beampatterns. IEEE Transactions on Signal Processing: 1–1. Available: http://dx.doi.org/10.1109/TSP.2017.2656840.
SponsorsThis research was funded by a grant from the office of competitive research funding (OCRF) at the King Abdullah University of Science and Technology (KAUST) under grant number URF/1/1713-01-01