Covariance Matrix Estimation for FDA-MIMO Adaptive Transmit Power Allocation

Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar produces an angle-range-dependent and time-varying transmit beampattern due to the small frequency increment across its array elements, which provides potential applications in new radar techniques. In this paper, we first establish a FDA-MIMO radar receiver model in the presence of spectral interferences, which focuses on the interference covariance matrix structure when the transmitted baseband signals are time- or frequency-domain orthogonal. Then, we show that the FDA-MIMO radar has a capability in suppressing spectral interferences with low computational complexity. Specifically, we propose an adaptive transmit weight vector for element-wise power allocation through maximizing the output signal-to-interference-plus-noise ratio (SINR). Furthermore, we propose a shrinkage-to-tapering algorithm for covariance matrix estimation in a coherent process interval. The interference-plus-noise covariance matrix is reconstructed accordingly with prior knowledge including the target, interference and noise covariance matrix structures. Numerical results demonstrate that the FDA-MIMO radar with adaptive power allocation can suppress spectral interferences by the developed method and high output SINR is achieved.