Multiple-input multiple-output (MIMO) radars may outperform other radar systems such as phased array radars, in terms of higher resolution, better detection probability in the presence of interferences, better parameter identifiability and more flexibility in beampattern design. Waveform covariance matrix design, because of its role in the beampattern synthesis process, is one of the most important problems in MIMO radar systems. In this study, the authors have proposed a closed-form solution based on Fourier series coefficients to design a covariance matrix. The resulting covariance matrix fulfils the practical constraints, i.e. positive semi-definiteness and the uniform elemental power constraint. It also provides performance similar to that of iterative methods, while requires lower computation time and provides better mean square error with respect to other existing closed-form methods. Eigenvalue decomposition is also utilised to convert the possible resulted pseudo-covariance matrices (pseudo-CM), which are not guaranteed to be positive semidefinite, into a covariance matrix. Simulation results show the performance of the proposed method.
Beam-pattern matching plays an important role in multiple-input multiple-output (MIMO) radars.In the vast majority of research done in this area, the aim is to find the covariance matrix of the waveforms fed into the transmit array. Also, reconfiguring a preset array of antennas (antenna selection) which means turning off some of the antennas in the array, is an effective technique to reach the desired beam-patterns, dynamically. In this paper, we introduce a novel multi-step method to implement this reconfiguration technique to a uniform linear array (ULA). In each step, by exploiting the relation between the diagonal elements of a covariance matrix resulted from solving a beam-pattern matching problem and the transmitted power of the antennas, we find the least important antenna of the array and turn it off accordingly. Then, we repeat this process until a predefined number of antennas remains.Our proposed method outperforms its counterparts in the literature in terms of beam-pattern matching as well as computational complexity, which makes it an appropriate method for real-time applications.Simulations used to show the validity and superiority of the proposed method.
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