Space-time adaptive processing with dictionary calibration based on iterative adaptive approach

Aiming at the off-grid effect caused by improper dictionary settings due to sparse recovery space-time adaptive processing (STAP), this paper proposes a dictionary calibration STAP algorithm based on iterative adaptive approach (IAA). Firstly, in each iteration of IAA, the atom corresponding to the maximum power of each quantized spatial frequency is found in the original space-time guidance dictionary. The Doppler frequency around the selected atom is evenly discretized into a set, and then the best atom is searched by maximizing the joint likelihood function in the local area, which is used to replace the selected atom. Finally, through the global iteration of IAA, the atoms matched the clutter ridge are selected to form a new space-time steering dictionary. Experiment results show that this method can effectively reduce the clutter ridge expansion caused by the off-grid effect, and the clutter suppression performance is better than the existing IAA-STAP method with uniform discretization of the space-time steering dictionary.