Space time adaptive processing for airborne MIMO radar based on space time sampling matrix

Different from the traditional airborne single-input multi-output (SIMO) radar, each array element of air-borne multiple-input multiple-output (MIMO) radar transmits mutually orthogonal waveforms, and mul-tiple array elements receive at the same time. A set of matched filters are used to separate the trans-mitted waveforms in the echo signal. When the elements of the transmitting antenna are close to each other, the airborne MIMO radar can gain the benefit of waveform diversity and produce a large spatial virtual receiving array. It has certain advantages in signal-to-noise ratio, spatial degree of freedom (DoF) and spatial resolution. In this paper, the clutter DoF estimation formula of airborne MIMO radar is given and can accurately estimate the clutter DoF values under different parameters. On this basis, this paper proposes a space-time adaptive processing (STAP) method based on space-time sampling matrix. This method utilizes the low rank characteristic of clutter covariance matrix, constructs the clutter covari-ance matrix based on space-time sampling matrix, and estimates the clutter power through subaperture smoothing. In the non-homogeneous clutter background, the method only needs a single sample to ef-fectively suppress clutter. In the homogeneous clutter background, as the space-time equivalent array is a dense non-uniform array, the robustness of the method is further improved by adding a small amount of training sample information. (c) 2023 Elsevier B.V. All rights reserved.