Tri-iterative STAP for transmit beamspace-based MIMO radar

Abstract

ABSTRACTBecause of the transmit power dispersion, the output signal-to-clutter-plus-noise ratio (SCNR) of the traditional airborne multiple-input multiple-output (MIMO) radar space-time adaptive processing (STAP) is severely restricted. To address this problem, a transmit beamspace (TB)-based tri-iterative MIMO-STAP method is proposed. First, the signal model of the TB-based MIMO radar STAP is established, and the TB matrix is designed based on spheroidal sequences to focus the transmit power within the spatial sector of desired targets. Then, the clutter-to-noise ratio (CNR) of the TB-based MIMO radar is analysed to show its relationship with the total transmit power. The calculated value is provided to illustrate that the CNR of the TB-based MIMO radar is reduced compared with the traditional MIMO radar with uniform omnidirectional transmission. Next, in order to decrease the training sample requirement and the computational complexity of the TB-based MIMO-STAP, the tri-iterative algorithm (TRIA) is employed to resolve the reduced-dimension weight vectors. The proposed TB-based tri-iterative MIMO-STAP method can achieve superior SCNR performance at lower computational cost, compared with the tri-iterative STAP for the traditional MIMO radar. Simulation results demonstrate the effectiveness and superiority of the proposed TB-based tri-iterative MIMO-STAP method, which is valuable for engineering application.