Exponential FDA-MIMO radar mainlobe jamming suppression based on DL-EVE algorithm

When the training data contains target signals and the target steering vector mismatch for multiple-input multiple-output with frequency diverse array (FDA-MIMO) radar, the performance of mainlobe jamming suppression will be sharply declined. Considering that the nonlinear FDA-MIMO radar has no grating lobes in the range dimension, an exponential FDA-MIMO radar jamming suppression method combining diagonal loading and eigenvector elimination (DL-EVE) is proposed, which make full use of the correlation between the target steering vector and the signal subspace. Simulations show that under the conditions of low snapshots and low input signal-to-noise ratio (SNR), compared eigenspace based beamformer (ESB) algorithm, the proposed method can still effectively suppress the mainlobe jamming and output a higher signal-to-jamming and noise ratio (SJNR).