Beam-space reduced-dimension space-time adaptive processing for airborne radar in sample starved heterogeneous environments

A method for selecting auxiliary channels in reduced-dimension space-time adaptive processing (STAP) is proposed for airborne multiple-input multiple-output radar. The auxiliary channel selection of the proposed approach is data dependent. Based on maximum cross-correlation energy metric, the significance of each spatial-Doppler channel is evaluated, and the auxiliary channels are selected step-by-step through utilising iteration. For the sake of achieving better performance as much as possible, the proposed approach will select two auxiliary channels at the first step, and select one channel at the next each step. Due to that the explicit physical meaning is very important for a STAP algorithm, the physical meaning of the maximum cross-correlation energy metric is discussed, and the fact that the local optimal output signal-to-interference-noise (SINR) performance can be assured by the maximum cross-correlation energy metric is proved theoretically. The simulations demonstrated that the output SINR loss of the proposed approach is about −1.9 dB when only two auxiliary channels are selected. Consequently, the proposed approach can reduce the requirement of the sample support dramatically. This will be more obvious advantage for the practical application in heterogeneous clutter environments where the number of secondary samples is extremely limited.