A robust STAP method for airborne radar with array steering vector mismatch

• A spatial-temporal integral covariance matrix is constructed by considering the mismatched DOA and Doppler frequency.
• The subspace corresponding to the clutter-plus-noise is extracted from the spatial-temporal integral covariance matrix.
• Clutter-plus-noise subspace is used for impose an appropriate constraint to estimate the actual steering vector.

In this paper, we consider the problem of space-time adaptive processing (STAP) for airborne radar in the presence of direction-of-arrival (DOA) and Doppler frequency uncertainties, either of which would result in steering vector mismatch. A robust STAP method is devised by introducing an accurate steering vector estimator. In particular, by considering the mismatched DOA and Doppler frequency, a spatial-temporal integral covariance matrix including the actual steering vector component is first constructed. The subspace corresponding to the clutter-plus-noise is then extracted from the so-obtained matrix and used to impose an appropriate constraint to estimate the actual steering vector. The resultant problem is a non-convex quadratically constrained quadratic program (QCQP), which is solved using the semidefinite programming (SDP) relaxation technique. Numerical examples are presented to demonstrate the performance of the proposed approach in different hypothetical scenarios.